Work is progressing on the new Brain Searchable Photo Index.
Here's a small example of its usefulness. Let's say you're
interested in the position of the small breadboard on the Parallax
Propeller Proto Board. You need photos to position it properly.
Do a PDF search and the following pops up:
PAGE POST
03....49, 50
05....100
06....102, 104
09....163
15....285, 289
Brain Speech Recognition
Talk to the Brain in your own language
Taking the advice of the original posts about filling the Brain, speech input as the recognition of spoken words will be added to the Brain's repertoire. The propeller is a powerful chip. With hardware from the Parallax Propeller Demo Board (now merged with the Brain Summit), speech input is possible just by adding some software.
According to Microcontrolled This program receives voice through the "RecordBase" PUB and then you can record through the "WaitForCommand" PUB and compare it with the previously recorded sample. This object can get it right 50% of the time. Since the command will only work with your (the recorders) voice this is more ideal for security programs then ones needing spoken commands. Mic in circuit is equivalent that of the one on the demo board. Thanks to Jeff Ledger and Raymond Allen for the objects they made that this is based off of. http://obex.parallax.com/objects/565/
Microcontrolled discovery thread http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project/page2
It works by taking your program and replacing the "Play" (although it can be put back in if you want playback, I did that) with a new "CheckRecording" subroutine. It has not only a WAV byte array, but also a "Final" byte array as well. The extra subroutine takes the first part of the "Start" routine from your program and the "Play" subroutine and combines them after the "Record" subroutine call in the "Start" subroutine. It then replaces the playing part of the "Play" routine with a function that checks the sound within a range that is set in the CON block. It reads it byte by byte in decimal mode and then once checked it writes them to temporary VARs. It is doing this in a repeat loop so the temporary VARs get overwritten every time it loops. Anyway it is reading the previous recording and the new recording at the same time, so that is what it is comparing. If it is in the set range (say, "40") then it writes +1 to the globel "sound" VAR. When it is done with this it checks for how consistent it is by guessing how many sound bytes where within range by a value set in the CON block. The value can be 0000 (none right) or 8000 (all right, impossible match) it does the comparison with a "=>" sign so it can be more exact, but not less exact.
Microcontrolled provides a demonstration video www.youtube.com/watch?v=7X_0wLvo0SQ
Here's the video! It is a bad video camera-wise, when I lean in to the mic to speak I move the camera out of view from the LED's. Has anyone tried it yet? I suggest adjusting the accuracy between 1800 and 4000 if it starts thinking that different words are the original word that was spoken. The thing about it is that it must be initialized. The sound waves must match the speaker's voice. That is what makes it possible to do on the Propeller. Also, the voice samples take about 10k of HUB RAM, however, I could add an SD card and be able to do a 1 time initialization by storing them on the SD card in a WAV file format.
According to Phil http://forums.parallax.com/showthread.php?115725-Goertzel-based-speech-quot-recognizer-quot-%28now-with-source-code%29
It requires a Propeller demo board and an attached NTSC monitor. That's all. When run, you will be prompted to say the words, "left", "right", "forward", "reverse", and "stop" three times each. Then you will be asked to say any of these words, one at a time. After each utterance, each word will be displayed with three scores, one for each training template, and a decision algorithm will determine which word you said. That's it. Nothing fancy. You can even substitute different words during training, if you like: e.g. their equivalents in another language, say, or the digits "one" through "five". Try it at different microphone distances. It's easiest to watch the monitor if you're not bent over the board speaking directly into the mic. I'm typically leaning back in my chair with the board on the bench. When training it on "right" and "left", try extending the length of your pronunciation, and emphasize the "l" and "r" sounds. That will provide a more detailed template. When testing, every utterance is stretched to fit the template, so the more detailed the template the better. A firend of mine stopped by this afternoon, so I had him try it with templates trained on my voice. It got about 75%, not counting the "say again, please" responses.
According to Oldbitcollector http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
Speech Recognition for the Propeller: Collaborative Project?? After seeing Chip's demo at UPEW I wanted to take his idea to the next level for some simple speech recognition for the Propeller. NOTE: This project is in very early stages! At this point it simply displays the recorded data and plays it back. It is based on Rayman's Parrot player. I'm using Propterminal so I can work in my livingroom. (Included in the zip) You'll need the demoboard with microphone (or equiv) to make this work. I'm looking to "loosely" match high points in the waveform, for simple one word commands. The command "LIGHTS" might turn on an LED.
Mike Green describes speech recognition
The Prop could do very simple speech recognition. The Apple II had simple speech recognition using a 6502 microprocessor and not a lot of memory. It recorded 8 bit sound in a buffer, normalized it, compressed it, and compared the result to a dictionary of previously recorded compressed sound samples. The accuracy was terrible although a very few carefully chosen words worked well enough for impressive demonstrations.
Mike Green: In the case off BASIC Stamps
Speech recognition is very complex and requires a lot of high speed analysis and the Parallax Stamps are just not suitable for that sort of processing. You would need to use a speech recognition processor and just use the Stamp to control it. One company that makes such a system is www.sensoryinc.com/products/vr_stamp_toolkits.html. Some of the "old" personal computers like the Apple II had simple speech input and pattern analysis programs that would take audio input, normalize it, and count zero crossings to get a measure of the dominant frequency. They would look for silences (to mark the beginning and end of words), then look in a previously processed dictionary to find the best match to the input. These programs would give fair accuracy for a vocabulary of a few words, maybe up to 10-15 words as long as the words were distinctive...
Zoot found a TAB book with a project to develop BINARY speech input http://forums.parallax.com/showthread.php?100739-Speech-Recognition
name for it "Fredian Grammar" -- for FREquency DIfferential ANalysis.
The book is an old Tab Book -- #1141 -- "How to Build Your Own Working Robot Pet", by Frank DaCosta. Circa 1979. The speaker (you) speaks an arbitrary tone of some loose duration (say anywhere from 1 to 4 seconds). The rough pitch of the tone is measured and set as the "baseline" (in software ONLY for the current run). The 'bot will then expect 4 subsequent "tones", again the durations and spaces are *very* loose. Any tone that is HIGHER in pitch than the baseline is considered binary "1"; any tone lower in pitch than the baseline is binary "0". The 'bot then has your Nibble recognized and decoded. In a sense it's an alternate form of auto-baud-detect serial communication, where the first "start" bit is used to determine the "settings" for the 4 bits to follow. The idea here is that no matter what the speaker's cadences and pitch (a child has a much higher pitched voice) the 'bot will adjust and decode the Nibble. I imagine it would be quite funny to hear in person -- you'd be saying things to your 'bot like "hooooom. ummmm. ahhhh. ahhhh. ummmm" (%0110).
DaCosta implemented his idea nearly 30 years ago. He uses an op-amp and measures the zero-crossing to get a rough pitch. I read the whole chapter and he discards pitches below 160hz and above 1250 hz (but he does his counting and frequency measurements with like 10 dip sockets' worth of latches, shift-registers and 555 timers -- all that could be in firmware). His "ideal" length for the reference and bit pitches is ~ 1 second, with a 1-4 second pause between each. That gives about a 20 second window for receiving the nibble -- if all the bits aren't received within 20 seconds or so, the input is discarded as a bogus transmission. The basic circuit is a crystal mic into a two-transistor buffer which feeds an op-amp for detecting the zero-crossing of the frequency. He chose Nibbles because he says 4 binary "digits" are pretty easy to remember -- going to 6 or 8 bits made it nearly impossible for him to "speak" without a chart. I would tend to agree -- 5-8 bits and you might need a cheat sheet. But given the non-limitations on the firmware, yeah, you could make the "vocabulary" as extensive as your brain could handle.
DaCosta's circuit measures the change -- the first 1 second "tone" received is the threshold. He does a sampling over 2ms and uses that as the "frequency" -- his circuit outputs a square wave TTL from the opamp based on whatever is being received by the mic. Then in software he just uses the count -- if he gets X pulses generated from the original sinusoidal soundwave that's the threshold. Subsequent "tones" are declared "1" or "0" if the count is higher or lower than the threshold.
Speech Input Tips from Beau Schwabe http://forums.parallax.com/showthread.php?100739-Speech-Recognition
Even if you build a basic one word command vocabulary and just have a few words, there are certain recognizable "patterns" produced depending on the choice of words used. Obviously there will be several words that might have similar patterns that you will want to avoid. Instead of focusing on the actual frequency, focus on the change in frequency (set a threshold and interpret this·as a HIGH or LOW)... sort of like FSK. Also combine this with amplitude patterns. Using just those two speech components might surprise you.
Beau describes another approachSpeech Recognition.doc http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
The discussion pjv, Oldbitcollector, and myself had at the EXPO about speech recognition relied more on looking at the integral energy for pattern recognition·more than the frequency of the speech itself.· If you capture the integral energy at specific time intervals,·and compare that to incoming data then the only normalizing that you need to do is adjust for the various rates that the word is spoken at.· This is a fairly simple algorithm to "expand" or "compress" the buffer length before the comparison is made against the stored data.· This method limits some of the words that can be used, i.e. similar words·will have similar energy patterns and can be difficult to distinguish.· But simple word commands will work just fine.
Leon describes the technique used on the TRS-80 http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
Low-cost speech recognition system like that which used to be available for use with the TRS-80 were very simple - they used a number of of bandpass filters (implemented with op-amps) with the outputs fed to comparators. The comparator outputs were sampled using an input port, and the samples compared to templates previously created in training sessions. IIRC, it could deal with 32 words. I spent some time playing with the TRS-80 unit and it worked quite well. Something like that could be implemented using an FFT. I keep meaning to try it with a dsPIC, it would be quite trivial.
Item Code 30080Add voice recognition functionality for 23 built-in pre-programmed or up to 32 user-defined commands. The Say it GUI software for the BASIC Stamp 2 provides an interface for training the module and producing template code. Or, use the robust serial protocol to access the Say It Module functions from other microcontrollers. Currently $59.99
New Fast Online Brain Search Index
Faster searching without the PDF File
I found myself constantly starting up the PDF to search for
specific Brain posts, and this was not the fastest procedure.
The idea came to mind about putting the info in a couple posts
for "search at a glance." The user can still go to EDIT in the
browser and select FIND and search the post to locate content.
It looks like everything fit into one post for homogeneous post
searching.
Page 1
#01 Humanoido: similarity to a human brain, vision processing, memory, autonomic nervous system
#02 P!-Ro: Use an extremely large array of sensors similar to that of the human nervous system.
#03 Leon: Consciousness.
#04 Erco: I would say that all the brainpower in the world needs to be supported by a robot with equally impressive sensors and mechanicals that use all that processing power to move around in and manipulate the world around it.
#05 Whit: keep "out of trouble." That is, keep it from running into things, running off drops or down stairs. keep itself powered, solar panels, calling out for help, trouble alarm. Basic robot safety (protecting itself) would be my first priority. I guess I would aim for the most basic brain functions first.
#06 TinkersALot: Tongue In Cheek Sardonic Grin Smart Aleck anthropocentric thinking human intelligence
#07 Humanoido: autonomic nervous system, react automatically, hot, cold, light, dark, hunger, full, touch, smell, noise, tilt, terrain, wind, hurt
#08 Sylvie369: NYT article link
#09 Humanoido: the brain can be bigger, faster and use more sophisticated AI
#10 Humanoido: Single skill evolution can become evolved, EXPO robots
#11 Lardom: Robot charging station
#12 Humanoido: Determine right from wrong, prioritize
#13 Humanoido: Personality mode
#14 Erco: A sense of duty
#15 P!-Ro: It can vote
#16 Humanoido: interpret the law, a philosophical center
#17 Humanoido: fuzzy logic, less rigid, average, approximate, result inconclusive, gray water, interpret vision, sets of general algorithms apply across the board
#18 Humanoido: snap decisions and judgements when there is limited or no time to think
#19 Humanoido: emotional center, interest heightened or lack, robust behaviors = interesting activities
#20 Humanoido: Transfer information, cog to cog wiring, special brain lobe
Page 2
#21 Humanoido: Thinking faster than original prop specs, internal pure thought should be the fastest
#22 Humanoido: algorithms to transport/understand information/thought, machine approximation
#24 Humanoido: smaller brain, model after the bigger brain, fit hobby budget/resources, go above and beyond the basics, basics include vision, obstacle avoidance, beeping, moving in some patterns, determining location/orientation, sumo, maze solving, wandering, not falling off ledge, ranging, mapping, accepting input from sensors, recharge batteries, beyond basics include thinking, reasoning, ability to resolve problems, accept new challenges
#25 Humanoido: Multi-Brain Concept a duplicate brain, help Alzheimer's, double brain power
#26 Humanoido: (brain in a brain) 2nd brain housed inside the 1st. Though I expect the ability to connect and disconnect brains on the outside would be a useful feature in times of service, debugging or expanding with more brains. Maybe if brains are made inexpensively, they could be discarded and recycled. With multiple brains come dedicated brains. Brains could be located anywhere inside the robot. How about off-the-shelf brains. Companies could compete to see who can make the best brain.
#27 Humanoido: a big brain can be filled with interconnected hybrid processors
#28 Humanoido: A Brain Chart, Brain Stem - route information via nerve center to mobility center
#29 Ratronic: where is the link to the brain chart?
#30 Humanoido: provided link
#31 Humanoido: 1st Hybrid Brain Processor working, 2 languages, 1st successful prototype brain stem
#32 Humanoido: Robotic Brain Stem (with photo)
#33 Humanoido: with photo, Adding the Brain Base to the Big Brain
#34 Humanoido: Robotic Brain Filler
#35 Whit: Please continue posting, very interesting. Don't let the lack of posting discourage you
#36 Humanoido: moved into the next phase which is the actual construction of the brain.
#37 Humanoido: A Working Robot Brain Blob! (with photo)
#38 Humanoido: The Next Brain Blob Addition
#39 Humanoido: Brain Blob Software (Blobber Code)
#40 Humanoido: Open Source
Page 3
#41 Humanoido: Proto Board Brain Surgery Technique to Reduce Power Consumption
#42 Humanoido: Soldering Brain Pins
#43 Jonlink0: action potentials that can be sent are excitatory, and each neuron only has an 8-cell (moore) neighborhood, "waves" of action potentials will grow chaotically from a disturbance in the medium. Some method of creating inhibitory action potentials (perhaps utilizing extra cell states?), as well as input/output methods (easily done by changing certain cell states according to the states of the robot's sensors), may cause interesting behavior. Some sort of inhibitory action potentials are obviously necessary to prevent the automaton from becoming saturated with chaotic activity, which is what Brian's Brain will default to if given semi-random sensor input.
#44 Humanoido: more processors ideal for neural net neuron simulations
#45 Humanoido: software with self reasoning power. It doesn't need to be an Einstein but some intelligence greater than a bug would be appreciated. Memory needs to be added, as so far the sum total is reference eeprom at 20 x 32KRAM. Propeller can access PC and the PC has TeraBytes of operating storage, use a server to provide wireless data storage. Web access can provide a knowledge base to work with.
#46 Humanoido: Brain Guts Data Light Convert Power LED to a Data LED (Parallax Propeller Proto Board)
#47 Humanoido: Brain Definitions as Applied to the Brain Blob The list of Brain components…
#48 Humanoido: Jumper Leads
#49 Humanoido: Brain Span Construction
#50 Humanoido: Brain Blobatory Breadboard Retrofit
#51 Mike G: you do not need a big brain. You need a big network with many specialized processor nodes.
#52 Humanoido: Open Source Project
#53 Humanoido: acting upon information received from some giant server.
#54 Mike G: use one specialized processors for vision, one for hearing, one for voice recognition, and one for speech. Abstracting these tasks makes the whole much more extensible and it allows a device to contain only the nodes needed to fulfill a particular task. Plus it would be easier to place the specialized nodes anywhere on the device.
#55 Humanoido: Brain Blob Preliminary Specs
#56 Mike G: why use a full or half duplex bus over say an 8-bit or 16-bit parallel bus
#57 Humanoido: Brain Stem is using a BASIC Stamp which is capable of doing one thing at one time, full duplex would be meaningless. Half duplex is an ideal match because it's dedicated to motor mobility functions which happen relatively slowly anyway. The Propellers run at full duplex, which do the
upper thinking and higher brain data transfers at higher speeds, hence the hybrid terminology. The master can treat 21 EEPROMs across the slaves as one distributed EEPROM equal to the sum of the individual parts.
#58 Humanoido: Processors tasked out to do specific jobs. Generally in the OBEX we see apps that run in specific cogs. Dedicating cogs/processors to these specific areas of the brain is entirely feasible. The human brain is tasked out in a similar fashion, i.e. a place for vision, motor functions, speech, memory, etc.
#59 Mike G: I can't wrap my mind around the logic it would take to coordinate such memory access
#60 Humanoido: The master can assign indexing to each prop board to define its location which gets stored into eeprom. Slaves and Master can access this global eeprom memory storage location to determine who's who and where they're located. These character maps are drawn out and stored in eeprom, then globally accessed. It's also simple to write a routine to pass variables and store them in specific eeproms. Access is by asking the slave for the information. The IC2 connection is transparently local to any requests and of no global concern.
Page 4
#61 Mike G: I see code executing in a COG on every Prop that deals with bus arbitration and some kind of packet protocol. You'll need a way to process and organize the disparate EEPROM data.
#62 Ravenkallen: develop a weather forecasting module
#63 NikosG: Brain1: Survivability e.g. by returning to a recharging station, or keeping itself in light where it could receive recharging through solar panels or tracking the solar panels (at this point I can contribute) Brain2: Ability to move autonomous and avoid obstacles, and also to choose the best way (Maze problem) Brain4: Ability to take a variety of measurements (use any kind of sensors) (I agree with "Ravenkallen") Brain3: remote communication with it master (ability to send data and receive commands) Brain5: Ability to perform task using a robot arm Brain6: Ability to transform Itself (change shape or leave some mechanical parts in order to achieve something). Have you ever thought your robotic "big Brain" to have a mechanism that can add or remove the aproppriate card in a specific socket?
#64 Humanoido: brain ground based exploration, process telemetry from the probe or satellite
#65 Humanoido: Processing/organizing disparate EEPROMs assigned to master or sub master
#66 Humanoido: legs move, fix things, small hands to reach/grasp, control, perform tasks
#67 Humanoido: tasking interface that could serve as a standard connection point to the outside world
#68 Humanoido: link to USB cable powers Protoboards not over 500mA, for testing and development
#69 Software Overview
#70 Hardware Development
#71 Humanoido: staid algorithms, maze solving, faster, more efficient/sensors, sensors at each side, special sensor - high up telescoping mirror looks at maze top down, ascertain solution differently
#72 Humanoido: shape shifting brain, works with software/hardware, brain carries its own tools/parts,
removing one assembly and attaching another, assemblies store in a spare brain cavity
#73 Mike G: some kind of a bootstapper to "Self Load" code into the multiple Props? Maybe similar to the ZigBee bootloader blog/post?
#74 Humanoido: software currently uses BASIC Stamp commands beginning at the first level of the Brain Stem which filters upwards through the Brain Base and on through the Brain Span
#75 Humanoido: bus single wire, two wire, parallel interfaces, self loading, eeprom, crystal propagation, leave room for future development like the first model T car
#76 NikosG: personal projects with vision, maze, comments
#77 Humanoido: personal projects comments
#78 More about the LED Mod (with photos)
#79 Test Software code used to test the LED modification on the Parallax Propeller Proto Board
#80 Power Regulator Modification (with photo)
Page 5
#81 Humanoido: data light will be installed in as many boards as possible. testing will be a separate project.
#82 Humanoido: follow LED mod installs, decoupling capacitor installation, decoupling capacitor test?
#83 Brain Blob (Dangerous Growth Spurt?) (with photos)
#84 Brain Blob Mods Complete (with photos)
#85 Test Software - Brain Blob Test (with code) BRAIN BLOB TEST.zip
#86 Decoupling Capacitor
#87 Testing Phase
#88 Troubleshooting Phase
#89 MikeG: sorry for the rant
#90 Humanoido: these hobby machines are designed to satisfy my purposes
#91 Troubleshooting Results All boards are Operational
#92 Revised Test Software BRAIN BLOB TESTb.zip
#92 Johlink0: my robot cellular neural network similar to Brian's brain, genetic algorithm to allow learning
#94 Humanoido: The sharing of these ideas will undoubtedly lead to something remarkable.
#95 Software Test 2 brainblobtest2led.spin
#96 Boards on Boards This is the board attachment phase
#97 Power Testing
#98 Testing Conclusions
#99 Micro photo of 241 resistor
#100 Small breadboards are added to PPPBs (photo)
Page 6
#101 Building DIY Breadboards A DIY project for Brain boards (with photos of breadboards)
#102 Testing setup for LEDs using breadboards (photo)
#103 Getting ready to add more breadboards to these PPPBs (photo)
#104 the last PPPB gets a solderless breadboard (photo)
#105 Humanoido: simple examples of learning algorithms, 1 Propeller, apply to multiple processors
#106 Jonlink0: Propeller Life object modify cell-changing algorithm from line 362 onwards
#107 Humanoido: The brain should be able to solve problems in which man never even thought about.
#108 Brain Blob BUS The foundation of the Hybrid BBB (with photos)
#109 Green Brain Blob & Green Guts Approach to recycling hardware and software (with photos)
#110 Brain Cog Power Draw Managing current within a Brain Blob (with illustration)
#111 Brain Work Sheet
#112 All About Brain Serial Interfacing Deciding nature of various connecting interfaces (hookup diagrams)
#113 Resistor Selection Propeller Protection & Pull Down Considerations
#114 Regulator (with hookup diagram)
#115 Barrel Power Connector Basic connections (with PPPB power section illustration)
#116 LED and Surrounding Territory Pictorial Map of LED on PPPB (with illustration)
#117 LED Schematic Sketch for modifying the LED (with illustration)
#118 Connector Pictorial Identifying the Propeller pins on the added connector (with illustration)
#119 PPPB Sketchings & Schematics Useful data notes for hookup (with illustration)
#120 Another Mod to the LED Secondary mod brings power consumption within reason
Page 7
#121 LED Second Mod To bring LED power draw into proper range (with schematic)
#122 LED Resister Determination for 2nd Mod
#123 Introducing Brain Replicants Modular Brain Pieces for Assembly
#124 Humanoido: self repair/maintenance, degradation, dedicated sections, growing memory capacity,
electrical signals, upgrading/evolution, combining components, role in society, function/purpose
#125 Humanoido: a ten year project of reverse engineering the human brain according to this source
#126 Human Brain Map References
#127 post reserved for books on building brains
#128 Pinout of First Connector
#129 Proposed Brain Concepts the current (in flux) brain concept
#130 Important Brain Concepts
#131 Reset Install Examination of method to install reset circuit (with photo)
#132 Basic PPPB with LED Mod Yellow lead from LED resistor to Propeller pin (with photo)
#133 Brain Span Constructed (with photo)
#134 Brain Span Working LEDs indicate functioning (with photo)
#135 Brain Span Troubleshooter Repairs made the next day
#136 Brain Span Animation Showing cycles of two LEDs per board (with animated photo)
#137 Increasing Brain Span Power Reliability Discovering settings to increase reliability
#138 Jumper Data Simplified wiring with jumpers (with photo)
#138 Brain Span Boards Clean Room Kept in dust-free containers (with photo)
#140 Brain Span Test Spin Simple software test for Brain Span brainblobtest3led.spin
Page 8
#141 Brain Span Serial Communications Bspan_send.spin, Bspan_receive.spin (with screen capture)
#142 New Brain Exoskeleton Structure A different kind of Skyscraper (with photo)
#143 Software with BS2 Functions For use with the Brain Blob
#144 Brain Board Configuration Try Out Formulating a final form (with photo)
#145 Nylon Spacers and Hardware Keeping minimal weight
#146 Brain Blob Resistors Revisited Establishing resistor values (with diagram)
#147 Open Season on Serial Objects Serial communications sources abound
#148 Brain Blogging http://forums.parallax.com/entry.php...-Brain-Project
#149 Brain Exoskeleton Redesigned New design improvements
#150 Online LCD Eavesdropping on the Brain's thinking (with photos of LCDs)
#151 Another Question - a Keyboard on your Brain what functions would you assign to each key?
#152 The 1st Propeller Desktop Brain Horizontal Computational Brain Machine (photo)
#153 Whit: Your documentation of this is amazing. I always learn something reading this thread.
#154 Humanoido: hope you can build a brain
#155 Brain Blob and BASIC Stamp Supercomputer Software Similarities are striking
#156 Utilizing Liquid Crystals - the LCD
#157 The Dream World Four types of brain dreaming
#158 Multi-purposed Software
#159 Case of the Missing Software
#160 The EXO: Exoskeleton Physical Form Factor Design Creating a new exo design
Page 9
#161 Connecting EXO Boards Avoiding short circuits (with photo)
#162 Solderless Breadboard Results Favorable results offer permanent solutions
#163 Solderless Breadboard Positioning The critical position is established (with photos)
#164 Dialectric Insulating Strips Design These prevent short circuits (with photo)
#165 Solderless Breadboard Inverted Testing Making sure the breadboards do not disengage
#166 Standard Brain Topology
#167 Time Table New time schedule in effect
#168 Invention of Brain Wrap When parts of your brain stick out (with photos)
#169 Design with Fewer Parts New design is more efficient (with photo)
#170 Optical Illusion One side appears space larger than the other (with photo)
#171 Round Robin Rings Schematic Brain Blob Basic New Design Connections (diagram)
#172 EXO Board Rows Showing the assembly of one EXO side (with photo)
#173 Brain Span Assembly challenge
#174 Right Angle Hardware Selection Angle iron connects Brain Spans together
#175 Balance Focal Point How to balance three brain spans
#176 Brain Span Analysis In terms of weight and wire length (with diagrams)
#177 Brain Span Configuration Making the decision to position weight and wiring (with diagram)
#178 Powering up 5-volt sensors in the Brain
#179 Brain Hybrid Form Factor Establishing a dual form factor brain
#180 Brain Photos Showing Hybrid Exo Configs Days experimenting - various EXO configurations
Page 10
#181 Pyramid Brain - Just for Fun (with photo)
#182 Brain Span Assembly Adjusting the hardware (with photo)
#183 Longer Bolts Create Stubs for Extra Attachments
#184 Getting ready to Program the Brain The 1st version Brain assembly comes into the light (phto)
#185 Brain Slots & Exo Expansion
#186 Brain Secondary Phase Expansion
#187 Injecting & Measuring Power Connector pin header (photo)
#188 Standoff Spacers as Brain Protection Devices spacers protect Brain in desktop modes (photo)
#189 Humanoido: connect human brains, solve brain disease, restore sight, extend human knowledge
#190 Angle Iron for Attaching Host Boards Keeping expansion in mind (photos)
#191 Contemplating Brain Spin-offs Mobility Brain, self modifying hardware, morphing
#192 Self Rewiring Brain A Brain could rewire itself
#193 Brain Card Racks Going with a simple conventional approach (photo)
#194 Brain Boombox Size comparison (photo)
#195 Host Boards Increasing brain capacity (photo)
#196 Brain Span Positioning Important positioning improves interface (photo)
#197 Brain Protection Use of spacers serve multiple purposes (photo)
#198 Brain Dashboard - Vertice Set Utilize vertice for convenient positioning (photo)
#199 Brain Blob Wiring Assembly line wiring of multiple Propeller boards (photo)
#200 Brain Color Coded Wiring Use of color simplifies Brain identifications
Page 11
#201 Brain Wiring Jumpers Establishing wire jumper details
#202 Brain Twin Expansion Using twin Props to expand the Brain (photo)
#203 The Fourth Brain Span Benefit results from creating vertices
#204 Brain New Wiring Concept Sketch brings new ideas for Brain functions
#205 Brain Software Nanites Programmable concept introduces small Brain effectors
#206 Brain Swarms Swarming inside Brains leads to Intelligence
#207 Brain Weigh In How heavy or light is the brain? (photo)
#208 Brains Top Mounting Hardware Brain can host boards at top or sides (photo)
#209 Brain Board Hosting Example shows hosting Brain boards (photo)
#210 Phil Pilgrim: issues
#211 Humanoido: addressing Phil
#212 Brain Thread and Posts Structure
#213 Brain Structural Support Open side receives structural supports (photo)
#214 Brain Feet Increase stability and protection with feet (photo)
#215 Brain Assembly Line Reference Board Increasing the speed and ease of assembly
#216 Brain Class Now you can attend class to learn more about machine learning
#217 Brain Projects Reports on other Brain projects are welcomed
#218 Brain Vertice Defined Showing how to use Vertices (photo)
#219 Brain Reference Board for Assembly Line Use a reference for faster assembly (photo)
#220 Brain Spin Code, Reduce LED Current, small program reduces power consumed by Brain data lights LED_reduction.spin
Page 12
#221 Brain Photo Size Increased photos may appear larger
#222 Brain Logical Addressing Idea for identifying locations (diagram)
#223 Brain Data Light Measurements Setup (micro photo, schematic, photos)
#224 Brain Neighborhood Identification Labels DIY your own Brain Labels (photo)
#225 Power Connectors and Power Test (photos)
#226 Duane Degn: robot navigation, laser scan surrounding, multiProps/cogs analyze, create 3D map, re mobile, switching voltage regulator- they are much more efficient than linear regulators
#227 Humanoido: addressing the wire wrap issue
#228 Brain Address and Identification printed labels for PPPBs (photo)
#229 Humanoido: switching LED power is vastly different
#230 Duane Degn: current & voltage analysis
#231 Power Reduction
#232 Brain Reinforcement Repairing the bent Vertice (photo)
#233 Brain Handles Adjoining spacers double in purpose (photo)
#234 Brain 1st LCD Selected for Output Parallax 4x20 serial LCD (photo)
#235 Brain 4x20 LCD Connection Hardware connects the largest LCD (2 photos)
#236 Brain LCD Spacing not to bump the platform surface during the Brain flipping process (photo)
#237 Brain Large LCD Mod Reversal of hardware facilitates Brain mounting (2 photos)
#238 Brain Nylon Board Connects Connects from board to board use nylon hardware (photo)
#239 Brain Board Insulator and Changes Protecting circuit pathways from short circuits (photo)
#240 Introducing the Flip Brain The flip brain concept for use in any Brain position (5 photos)
Page 13
#241 Two Brain LCDs Intro of 2nd LCD serves multiple purposes (2 photos)
#242 Center Brain Span Reinforcement Center Span flex requires strengthening (2 photos)
#243 Peripheral Adapter Module A platform to hold and attach additional Brain peripherals
#244 Brain Construction - Transparent Plastic Common resource material for construction (photo)
#245 Brain LCD Prepping Small preparation before use (2 photos)
#246 List – projects & products with tiny solderless breadboard
#247 Brain Bagging Bag it - Brain bag your boards for longevity (photo)
#248 Brain Plumbing & Cryogenics Brain installation of piping and routing of service tubes (photo)
#249 Search for Brain Cryogenic Temperature Sensor (6 photos)
#250 Cryogenic Brain Fuels Examination of coolants and effects
#251 Brain Bundle Nerve Distribution (photo)
#252 Brain Hybrid Wiring Establishing a Truth Table for Communications Interfacing (diagram)
#253 Getting Started Brain Phases Checklist 1st Checklist for assembly showing Brain Phases
#254 Brain Schematic Drawing Program Finding a new drawing … (6 photos)
#255 Brain Drawing Program Selection The current choice of programs being explored (2 photos)
#256 Brain Cryo Development Brain Cryo material & removal (photo)
#257 Brain Breather 1 Weekend Brain development Update
#258 Brain Top Mount Real Estate Brain real estate at a premium (photo)
#259 Brain Open Span Board Move Moving a brain board on the open span side (2 photos)
#260 Brain Peripheral Adapter Mount Connecting the mounts (photo)
Page 14
#261 Brain LCD Repositioning Improvements to mounting the larger LCD (3 photos)
#262 How to Build a Brain LCD Mount Photos show left and right mount details (3 photos)
#263 Brain Summit Construction of the Brain Summit (3 photos)
#264 Brain 1st Cockpit Outline Cockpit Instrumentation Control Panel Design Ideas
#265 Brain Small LCD Repositioning Increasing Brain board density (2 photos)
#266 Brain Increase in Board Density
#267 Brain Outer Skin Cowling Outer Skin is introduced (photo)
#268 Current Brain Configuration
#269 Brain Summit Board The peak gets a new board! (photo)
#270 Brain Business End Definition of Brain Business End position (photo)
#271 Connecting the Brain Summit Board Hot melt glue is one possibility
#272 Brain Space Telemetry Designs for Telemetry of Brain Cockpit
#273 Duane Degn: project concepts, display, data, boards, communications, loss of spring constant
#274 Humanoido: photo size
#275 Humanoido: response to Duane
#276 The Brain CEO Board Expanding and positioning (photo)
#277 Duane Degn: photo size
#278 Duane Degn: photo beautiful
#279 Humanoido: enlargement in FireFox
#280 Brain Tests - TinyCAD Drawing Program Analysis TinyCAD as Brain drawing program
Page 15
281 Brain Design - Diagram Designer Designs.. Diagram Designer selection & analysis (2 photos)
282 Brain Schematic Elements List of Brain circuit schematic symbols required
283 Schematic Symbols Defined There is no standard so this is a suggested guide (2 photos)
284 Brain Breadboard Virtual Prototyping with Pebble Draw Brain circuits.. (photo)
285 Attaching the Brain Summit Board Hot glue anchors the Summit Board (2 photos)
286 Brain Board Numerical Increase New board total and arrangement
287 Brain Breadboard Virtual Prototyping with Fritzing for BASIC Stamp/Propeller Chips! (photo)
288 Drawing Program Threads For Brain diagram drawing program research
289 Brain's Tiny Breadboard information about the Brain Tiny Breadboard (3 photos)
290 Brain Name Exploring the evolution of the Brain name
291 Brain I/O Ports as Sensors Ideas for I/O - touch sensing and nerve response
292 Brain Search Index Part One Brain thread Index by page, post number, content (photo)
293 Brain Posting Additions Method adds information to previous posts
294 Brain Processor Online/Offline Technique Method alters electronic Brain processors
295 Delegating Brain Components Brain components can reside in 3 places
296 Brain Peripheral Adapter Module Suspended New method speeds up development
297 Brain TV is a Reality Connecting TV via the internal stomach (2 entire brain photos)
298 Electronics & Electrical Tutorials as Brain Resources
299 New Brain Resource Cognition Cognition newsletter directly relates to Brain project (photo)
300 Brain AI News - Supercomputer Plays Jeopardy Machine playing against humans (photo) Page 16
301 Propeller Brain Self Education Tutorials for Propeller Programming
302 Brain Searchable Photo Index Nearing completion
303 Brain Speech Recognition Talk to the Brain in your own language
304 New Fast Online Brain Search Index Faster searching without the PDF File
305 Creating Brain Speech - Parallax Propeller Takes the Lead as Speech Synthesizer Chip
306 Brain Senses - Focus on Vision Part 1 Color, Light Intensity, Ultrasonics (6 photos 1 vid)
307 Brain Senses - Focus on Vision Part 2 Image CAM, Object Detection, Infrared (5 photos)
308 Brain Senses - Focus on Vision Part 3 Human Detection (1 photo 1 vid)
309 Brain Capacity Question
310 Brain Capacity Reply
311 NMR Brain Map Neural Map & Interactive Brain Basics
312 Watson - Artificial Intelligence Brain Wins Jeopardy over humans (1 photo)
313 Brain Top Down Organization Organizing Brain modules
314 Brain Outer Skin Protection for wiring (1 photo)
315 Brain Inner Skin Covers TV (1 photo)
316 Installing Brain TV Simple methods to install tv (2 photos)
317 Celebrating The Brain's First Light Unveiling the Brain's 1st functions on TV (2 photos)
318 Brain Project Status Report on the current Brain Project (1 photo)
319 Play Chess Against the Brain Sources for Prop Chess (2 photos)
320 Brain Fresnel Tests Enlarging the image of a Parallax 3.5-inch TV (3 photos)
Page 17
321 Brain Color BASIC Programming Language - Adding Extended Color BASIC 1.0
322 Brain Text Test Demo
323 Brain Wireless Communications System - Connecting peripheral robots via wireless interface
324 Brain Receives Board 23 - Parallax board serves wireless transmit/receive
325 Spectacular Giant Brain Fly-Through! - Travel through the Brain's Inner space..
326 Brain Project Selects Google 3D SketchUp - Apps developed with free open source 3D package
327 Brain Senses - the Electric Tongue - Focus on Taste
328 Brain On EmbeddedBASIC - Adding languages to the Brain
329 Brain Voice Amplifier - Audio amp supplements headphones
330 Brain Sub-Index - Page 17 - Faster sub index gets pasted into the master index
331 Singing Brain - Brain singing on video with audio track
332 Opening Up Brain Channels - Brain is capable of multi channels
333 Brain Achieves Cellular Automatronic Life - Propeller Program gives life to the Brain
334 Brain Cellular Automaton Life Options - Screen, algorithm, resolution, cell, evolution
335 Brain Offsetting Technique - Maintaining multi-processing purity
336 Brain Talking Keyboard - Input by hearing the keys
337 Brain Lips - Vocalization sound series
338 Brain Automaton Singing - Beginning of Automatonic Brain Song
339 Teaching the Brain to Count - Regular, Slow & Slow-Fast Counting
340 Sovr: amazing project, working on moods
Page 18
341 Brain Mood 1st Considerations - Psychological state of mind
342 iBrain On LOGO for Unfolding Dream Worlds - Dimensionally Dream with LOGO
343 Brain X-RAY Machine - Developing Brain X-Rays now a Reality
344 Brain TV Tuning for BIG Characters - How to tune a TV driver
345 Brain Thought - Program bouncing in multi cog systems
346 Machine/Human Brain Time Travel - Speed up and slow down brain time
347 Mike G requesting code
348 Humanoido asking if MikeG wants to spend time on it
349 Mike G apologizes
350 Cde use a simulation
351 Humanoid re: code
352 Humanoido re: simulation
353 Brain Base Communications - Design, code, schematics, tests
354 Brain Geneology - From Stamps to Propellers
355 Brain Stem Communications - Revealing Brain Stem test code
356 Brain Appendage Mobility Contemplation
357 Cde simulator, floating point
358 Deriving the Brain Dream Equation - Moving closer to real Propeller dreaming
359 Integer Brain
360 humanoid re: integer, logo
Page 19
361 Cde re: data processing, fixed or float
362 Humanoido re: AI wish list
363 Cde re: need evolutionary software
364 Humanoido re: Six Objectives of Machine Intelligence
365 Prof_Braino re: float is less precise
366 Humanoido re: float etc.,supporting links
367 Six Objectives of Machine Intelligence
368 Prof_Braino re: dreaming is information digestion
369 Prof_Braino re: fixed point calculations
370 Humanoido re: dreaming benefits
371 Humanoido re: collective FP errors
372 The Benefits of Dreaming - The commonality of advanced life forms
373 Six Points of Dreaming - Paving the way towards AI dreaming
374 The Dream of AI
375 Multiple Life Permeation - Fitting life in multiple cogs
376 Brain Monolith Discovery Emergence - The Matrix Monolith emerges from within
377 Brain Dreaming from 2D to 3D - New ELICA LOGO opens up a new realm
378 Propeller Brain Neural Design Moves Forward - The building of neurons
379 doggiedoc (Paul) re: neuroanatomy
380 Humanoido re: cautionary AI (story)
Page 20
381 doggiedoc re: recognition
382 Brain Artificial Intelligence through Gaming - Tic Tac Toe Neural Net
383 Phil re: link showing what 21,000 neurons can accomplish
384 Humanoido re: neurons needed/not needed
385 Martin_H re: california sea slug
386 Phil re: sea slug joke
387 Brain Research - Sea Slugs Computer Modeling
388 Brain Ear 1st Experiments - Mic sound input for analysis
389 Brain Life - Utilize BrainBox Neural Net to Establish Life
390 Brain Progress Report March 2010
391 Brain Dreaming Suggestions - Information Digestion
392 The Problem with Life - Creating expansive Brain life in a non-adiabatic system
393 Ttailspin re: superstitious brain
394 Humanoido re:superstitious brain
395 Brain Superstition in a Neural Starved Life Form - What are the odds with finite Propellers?
396 Brain Breakthrough - a Multi-Propeller Neural Injector (MNI) - Case of the evolving hybrid
397 Brain Matter Injector BMI - Machine injects & distributes neural matter
398 prof_braino re: alarming parts failures
399 Humanoido - Breadboard quality
400 - Brain Neural Fire - Artificial Intelligence Expert System Construct to Mimic Neural Fire using Software
Page 21
401 Brain Self Consciousness - I think therefore I am
402 Brain Turing Test - Fact or Folly?
403 Phil re: cheap parlor trick
404 vaclav_sal re: project suggestions
405 Humanoido re: The AI of ELIZA
406 Phil re: against ELIZA as AI
407 Duane Degn re: book comments, John McCarthy
408 DoggieDoc re: Jeopardy question
409 Mike G re: difficulty of AI, Penrose's "The Emperor's New Mind"
410 Humaoido re: Jeopardy status
411 The Jeopardy Factor
412 The Genius of AI - ELIZA Conversationalist
413 Mike G re: specific tasks quickly with high precision is not AI
414 WHAT IS ARTIFICIAL INTELLIGENCE?
415 AI Conversationalist
416 Duane Degn re: AI
417 Humanoido re: AI sources
418 Big Brain Begat Bantam Brain - Offspring Lineage continues
419 Mike G re questions
420 Brain Transfer & Life Extension - Today's technological levels
Page 22
421 Clever Programming
422 Paul re: washing machines
423 Duane Degn re: humans vs machines
424 Mike G re: a little randomness seems intelligent
425 Mike G re: personal opinion AI and Strong AI
426 Duane Degn re: McCarthy's book
427 Phil re: clever programming is not enough
428 Can a Machine Go Beyond Its Programming?
429 Humanoido re: which book?
430 Mike G re: personal opinion
431 Phil re: personal opinion
432 Humanoido re: posted code, NDA, open source
433 Humanoido re: query
434 Phil re: interrogatives
435 Humanoido re: AI programming details
436 Brain Evolution Programming
437 Humanoido re: washing machine humor
438 Leon re: Penrose subscribes to Hameroff's theory- the brain is a quantum computing system
439 Prof_Braino re: defining the nature of AI
440 Mike G re: AI is what you see in the movies
Page 23
441 Prof_Braino re: What you see in the movies is a cheap McGuffin
442 Mike G re: personal opinion
443 Prof_Braino re: the AI project, Brain etc.
444 A Great Voyage - The uncharted space of brain technology
445 Brain Historical Foundations - Part 1
446 Current Brain States - Small, medium and big
447 Brain Historical Foundations - Part 2
448 Brain Historical Foundations - Part 3
449 Brain Historical Foundations - Part 4
450 SEED to Brain Comparison
451 Twin Brain - 2nd brain twins the first
452 Establishing Neural Brain Power
453 NMI's as Discrete Brains - Neural Matter Injectors are multi-purposed
454 The Establishment of Machine Life
455 Mike G re: There's a lot that goes into opening a door
456 Humanoido re: additions to opening a door
457 Duane Degn re: teaching a robot
458 Brain Neo Cortical Columns
459 Phil re: personal opinion
460 Humanoido re: fractal sources
Page 24
461 Phil re: blocked sites
462 Humanoido re: point is reinforced
463 Phil re: quoting souces
464 Erco re: move on
465 Humanoido: divert resources to better use
466 The new 208 Brain - Another robot Brain is born
467 Brain Matter Folding - Can you fold an electric brain?
468 Phil re: personal opinion
469 Humanoido re: this is an open source hobby (personal use & enjoyment) development
470 Phil re: personal opinion
471 The New Brain 216 - Third Brain Now Under Development
472 Phil re: personal opinion
473 Martin_H re: why do this in hardware?
474 Hardware Software Hybrid
475 Brain Control Panel - Progressing conceptual development
476 New Brain Breadboard Design - Maximize breadboard space used
477 Mike G re: questions
478 More on the Smartest Boe-Bot Project
479 Humanoido re: answers
480 Mike G re: questions
Page 25
481 Humanoido re: answers
482 More on Brain Channeling
483 Humanoido re: answers
484 More about the Neural Matter Injector
485 humanoido re: answers
486 Brain Demo Day - Scientists in China get a glimpse
487 Mike G re: questions
488 Ttailspin re: answers
489 Humanoido re: US40 and Boe-Bot
490 Humanoido re: Brain Channeling
491 Humanoido re: interfacing info
492 Humanoido re: question
493 Mike G re: questions
494 Humanoido re: response
495 Brain Channeling Sources
496 Intro to Interfacing Reconfiguration
497 Humanoido reply to Mike G
498 Humanoido reply to Mike G
499 Humanoido reply to Mike G
500 Prof_Braino comments
Page 26
501 Phil comments
502 Concatenating Brains - Unexpected Brain surplus creates a mammoth Brain!
503 Brain Machine Biology - A symbiotic union of technologies
504 Brain Breaks 100 Processor Chip Barrier! Setting new record, largest Propeller chip machine
505 Brain Propeller Chip Reliability - Parallax Achieves 100% Reliability
506 The Next Generation Brain NGB - A quantum leap of processors
507 A More Manageable Method of Brain Connection
508 Brain Containment - Recycling Appliance Machines
509 Brain LED Array Redesign - New circuit helps offload Propellers
510 Experimenting with the Brain Modular Array
511 Brain Hosting at Max
512 Brain Ultra-Low Power Circuits
513 Brain Multiple Crystal Switching - Simple method for switching test crystals
514 Phil comments
515 Duane Degn comments
516 Humanoido comments
517 Phil comments
518 Mike G comments
519 Brain Crystal Options
520 Mike G comments
Page 27
521 Brain BUS Workings
522 Brain High End Crystal
523 Machine Learning with Lerner - Dave Hein fills a small brain!
524 Mike G comment
525 Humanoido comments
526 Brain Neural Matter Quanta NMQ Defined
527 Brain Neural Matter Quanta NMQ Phase Begins
528 Brain Neuron Output
529 Brain Neuron Quanta Density
530 Concatenation of Propeller NMIs Begins
531 Brain Neuronal Matter Defined
532 Construction of the 1st Brain Machine Neural Device - Making the first neuron
533 The How & Why of Cloning Neurons - Neurons are now being Cloned
534 Ramifications of a Cloned System
535 The many Faces of a Neuron
536 Embedding Machine DNA into the Machine Neuron
537 The Distribution of Neurons in a Machine Brain
538 The Creation of a Synaptic Net in the Brain
539 Machine Brain Synapse Comes Online
540 Second Man-made High Density Board HDB Under Construction
Page 28
541 Big Breakthrough in Machine Brain Technology! - 100,000 Neurons into 1st 100 Propellers
542 Brain Neural Partitioning
543 Neural Net Wiring
544 Neural Injection Design
545 Increasing Neural Net Partitioning
546 Brain Breakthrough! 100,000 Neurons Exceeded - Moving the Giant Brain to the next generation
547 Ttailspin congratulations!
548 Leon questions
549 Humanoido comments
550 Brain Machine Objectives
551 The First Brain Neural Net
552 Phil comment
553 Brain Support Computer is Down
554 Dedicated Brain Support Computer
555 Brain Signal Divide Points
556 DBSC Dedicated Brain Support Computer Selection
557 Brain Signal Divide Point Conditioning
558 Ubrupt Unfortunate Brain Project Termination
559 Martin H use forum & gmail for uploading copies, backups
560 Leon about digital vault backup
Page 29
561 Ttailspin comments
562 Mike G comments
563 Phil uses Knoppix CD
564 Brain Posting & Virus Update
565 Brain Files & Drive Update
566 Phil comments
567 Humanoido comments
568 Functioning of a Complex Machine
569 Phil Knoppix comment
570 Humanoido comment
571 Phil comment
572 Brain Situation
573 Alsowolfman source from scalpel linux to help recover files
574 Brain Computer & Hard Drive Updates
575 Ttailspin comments
576 Humanoido comments
577 Brain Hard Drive Attempted Restoration Update
578 Brain Drive Schedule
579 New Brain Drive Selection
580 The Problem with Backup
Page 30
581 Microsoft Windows is Now Ditched
582 Brain Oriented LINUX & UNIX Training Begins
583 IBM LENOVO ThinkPad Computers Now Trashed
584 Brain's New Computer Selection Nears Finalization
585 Brain is Hermetically Sealed
586 Brain EEPROMs Retain Code
587 Phil comments
588 Martin H humor
589 Humanoido humor
590 Brain Update 04.19.11
591 Brain OS Choices - Examining numerous OS choices
592 Brain Repurposing
593 Developing a New Brain Layering - NB Possible Cancellation
594 Brain Update 04.20.11
595 Brain Layering Computer Design Increase
596 Brain Computer Multipurposing
597 Brain Photos Batch Retrieval
598 "Brain is Back" Campaign
599 New Brain Lab Foundation Announced
600 Working on Brain Wiring
Page 31
601 Ttailspin comments
602 Phil bypass capacitors
603 Brain Posting
604 Big Brain Moving to America
605 Wire Leads Project
606 Mike G questons
607 Humanoido comments
608 Brain HD Update 04.21.11
609 Mike G comments
610 Brains Are Us
611 Brains at the Store - Trip to store has shocking results
612 Brain Computer Could Stall Project
613 PROLOG Added to Brain
614 Building a High Density Brain Breadboard - the solderless kind...
615 Brain New Netbook Stats
616 Ttailspin comments
617 Mike G comments
618 Humanoido comments
619 One Massive Brain Collection - Adding Up Props
620 Mike G comments
Page 32
621 Humanoido comments
622 Mike G comments
623 Brain Drive & Computer Update 04.23.11
624 Phil comments
625 Brain Index Awareness Day
626 Brain Drive & Computer Update 04.23.11b
627 Dave Hein comments
628 Phil comments
629 Humanoido comments
630 Humanoido comments brain index
631 Phil comments
632 Humanoido comments
633 Phil how to link a post number
634 Dave Hein comments
635 Publison comments
636 Humanoido comment post link update
637 Humanoid iphone posting, blog, robotics
638 Humanoido comment
639 Brain Drive & Computer Update 04.25.11
640 Brain Drive & Computer Update 04.26.11 - The Brain's Lost Files
Page 33
641 Remote Brain Posting - Carry your posting "computer" in your shirt pocket
642 Online Brain Index Updated to Page 33
643 Brain Add On Computers - Are they useful?
644 Phil comments Lenovo, T32, WinXP, Mandrake Linux
645 Humanoid commentspc without CDs
646 Stats on the Restored Hard Drive - the Brain Wins! Almost nothing is restored
647 Schematic Request Related to Brain Development
648 Phil comments how to retrieve attachments
649 Humanoido comments
650 Apple AMD Radeon HD 6750M Graphics Card 480 Stream Processors
651 Brain Gets Apple Mac Computer
652 Stepping up the Big Brain
653 Brain Config in April
654 Brain Config in May
655 Brain Programming Languages Selection SPIN, OPENCL, PBASIC, PASM, XCODE
656 Brain Relegated to ProMac Symbiotic Union
657 New Ideas for Autonomous Brain Backup - Cloning from Backup
658 Robotic Brain Mobility & Robotics
659 Zoot comments trademarks
660 Brain Naming Conventions
Page 34
661 Big Brain Design Breakthroughs with PROPELLERS & MACS
662 Big Brain Gains Utilizing Hard Drives
663 Big Brain's Supplanted Memory
664 Brain Programming in XCode 4
665 *** Change in Brain Project Development ***
666 Phil comments less stream of consciousness
667 Duane Degn comments
668 Mike G comments you're working on the cutting edge
669 Brain Project Overview - Props and computers
670 Humanoido comment
671 Humanoido comment celebration
672 Phil comments incredulous
673 Dave Hein comments be patient Phil
674 Is Brain DNA Genome Possible?
675 Brain Life Power Challenges & Considerations
676 Big Brain Genome Maps Instead of Schematics
677 Parallax-Propeller-Equipped Brain Genetic Machine Genome Project
678 Big Brain Sex - Is the Big Brain Hermaphrodite, Male or Female?
679 Humanoido comments grasshopper
680 Big Brain Propeller Waves - Different clocks for different blocks
Page 35
681 Build a Big Brain Propeller Qualitative EEG Machine - Measure Big Brain's Brain Waves
682 Big Brain EEG Machine as a Diagnostic
683 Leon comments neuron example to solve xor problem
684 Big Brain State of the INIT-Neuron
685 Phil comments
686 Leon comments ANN, Hull University, MSc project, Dataglove, BAe, MAD, Brough
687 Humanoido comments
688 Mike G comments asking for neuron code
689 Leon comments Here is a neural net toolbox for Scilab
690 Humanoido comments not posting code
691 Links to Managed Neural Projects
692 Mike G comments
693 humanoid comments no posting of development or test code for the reasons cited
694 Dave Hein comments you have expressed a lot of good ideas
695 Humanoido comments Brain development or documenting partial Brain development
696 Jazzed Tetra Prop Spins Brain Life Ideas
697 Dave Hein comments on posting code
698 Duane Degn comments on his great projects!
699 Brain Methodology
700 Humanoid comments to Dave Hein
Page 36
701 Potential of Connecting the Degn Massive LED Array
702 Future Brains with Afflictions - The 1st Guide to Machine Intelligence Sickness
703 Duane Degn comments about LED Array
704 Machine Brain Neurons and Neural Matter - New Brain Dictionary Definitions
705 Refinement Brain's Hybrid Interface - Successful Sharing Hybrid results in fewer wires
706 Brain Neural Complexity - Adding to the Brain Dictionary
707 Dictionary of Propeller Machine Brain Terms
708 Big Brain's Hyper Neural Threading HNT
709 Big Brain Domain Partition - Propeller DPs increase volume performance
710 Propeller Brain Change with Supporting Computers
711 Leon comments TFLOPS
712 What is the Giant Brain? Propeller or Other?
713 Leon comments simulate the ANN on the Mac
714 The Propeller ANN Mac
715 Propeller Brain Mac GPUs Selected
716 Many Faces of the Giant Propeller Brain
717 Moving Toward Ultra Brain with Props & Macs
718 Giant Brain TFLOPS
719 Leon comments 5,000 I/Os
720 Big Brain Backup Terabyte Drives
Page 37
721 Massive Propeller Brain Trinary State Output Device - a plane with quadrillions...
722 Brain Merging with the Massive Transposition Machine
723 Big Brain BOSS - Brain Operating Software System
724 Brain Doctor Meeting 05.14.11
725 AI Quotations
726 ElectricAye comments Kurzweil, Chinese Room
727 Humanoido comments Chinese Room
728 New Type of Propeller Simplex Neuron SN - Modified INTNeuron and Test Neurons? (with pseudo code)
729 Phil comments problem with early AI research, top down, bottom up
730 Reverse Engineering Evolution
731 Giant Machine Brain Eats Propellers
732 Little Parts - a Machine in the Machine - Isolate your brains
733 ElectricAye comments
734 Dave Hein comments modeling nerve cells
735 Phil comments cannot simulate intelligence without considering environmental factors
736 Leon comments consciousness
737 Phil comments unique possession of consciousness
738 Leon comments qualia
739 Time Stamping Human Evolution
740 Humanoid comments human consciousness and pure thought
Page 38
741 Mike G comments neurons, simple neural net
742 Defining Consciousness
743 ElectricAye comments
744 Exploring the Neural Net with the Simplex Neuron
745 Phil comments code
746 Programming to be Self Aware
747 Humanoido comments intention is to release BOSS when it reaches BETA
748 Controlling the Brain with Light
749 Mike G comments neurons
750 Simplex Neurons
751 Phil comments
752 Humanoido comments to Phil
753 Big Brain Self Rewiring
754 BST and Mac
755 Mike G comments neuron memory
756 Mike G comments neuron memory
757 Handling Neurons
758 NEURAL BRAIN MAP
759 Mike G comments neuron memorny
760 Phil comments source code
Page 39
761 Brain Map Revisions
762 Mike G comments on muffler wiring
763 Brain History & Challenges - Historical roots, humanoids, multi-processing machines
764 Humanoido comments car forum
765 Mike G comments
766 Determining Memory Usage
767 The Uphill Computer Journey
768 Mike G comments neuron memory
769 Humanoid comments neuron size matters
770 Mike G comments
771 Humanodo comments
772 Phil comments
773 Humanoido comments
774 Big Brain Index Update
775 Mike G neuron like spin code
776 Phil comments
777 Humanoido comments
778 Humanoido comments
779 The Big Brain Propeller Neural Map
780 TeraByte Propeller Brain Drives Arrive
Page 40
781 Big Brain Mirrors - No Glass
782 Big Brain Self Awareness - Making the Machine Big Brain Self Aware
783 Dave Hein comments on self aware
784 Doggidoc Paul comments on self aware
785 Self Awareness Early in Life
786 Humanoido comments to Dave Hein about Learner
787 Dave Hein comments about Lerner
788 Phil comment about Lerner
789 Humanoido comment about Lerner
790 Dave Hein comment about Lerner
791 humanoido comment about Lerner
792 Brain Child - More about the begotten brain child
793 Principle Parts of the Brain
794 Setting Standards of a Big Brain - First Intro of Functions
795 Zoot comments spelling
796 Humanoido comments spelling
797 Brain Gastropod Locomotion
798 Brain Mobility Through Snailing
799 Robots in a Brave New World Need a Brain
800 Brain Parts - the Next Level
Page 41
801 Big Brain in June
802 Baby Brain - Child Brain Leads to Baby Brain
803 Big Brain on the Multiple Props Projects List
804 ElectricAye
805 Brain Chip Independence Day - Neural Matter Independence and benefits
806 Humanoido
807 Automatic Brain Repair by Optical Illusion - Can a Machine Brain repair itself?
808 Big Brain to Increase Vision Processing Speed
809 Perceptions in Machine Vision - Arrow left or arrow right?
810 Ttailspin
811 Duane Degn
812 Doggidoc
813 Humanoido
814 Erco
815 Humanoido
816 Propeller Brain Subdomain Test Segmenting - Creating a subDomain
817 Big Brain Evil, Scary & Sarcastic Sides?
818 Big Brain Peripheral Enumeration - Six pin Enumeration
819 Brain Enumeration & subEnumeration
820 Intro to Propeller Big Brain Fluid
Page 42
821 Dave Hein, the illusion
822 Phil
823 Humanoido
824 Phil
825 Humanoido
826 Enumeration Schematic - 6 pin method with two lines
827 Dave Hein, using 4 pins tertiary
828 Trinary Enumeration - Using the float/limbo state
829 Brain Speed Doodle
830 Phil
831 Humanoido
832 Constructing a Transparent Plastic Brain Base - For Child & Baby Brains
833 Jazzed, another brain collage
834 Humanoido
835 Brain Travel Voltage Tip
836 The Magical Brain Partition - Big Brain will loan his chips to others
837 Big Brain Goes On the Multi-Prop List
838 ElectricAye
839 Jazzed, Turing test
840 Leon, take over the world
Page 43
841 Ttailspin
842 Jazzed, nothing wrong with art
843 Mike G, impressive work
844 Jazzed, turing test
845 Mike G
846 Jazzed
847 Phil
848 Jazzed
849 ElectricAye, Turing test
850 Jazzed
851 Mike G
852 Jazzed
853 Propeller Neural Net Conception
854 Ttailspin
855 Humanoido, machine deception not required
856 Jazzed
857 Phil
858 Humanoido
859 Jazzed
860 Ttailspin
Page 44
861 Jazzed, links
862 Publison
863 Robotic Big Brain
864 Humanoido, Lerner
865 Jazzed
866 Humanoido
867 Humanoido
868 Jazzed
869 Martin H, upload code as backup
870 Phil
871 ElectricAye
872 Jazzed
873 Phil
874 Leon
875 Martin H, neural net skepticism
876 Mike G
877 Ttailspin
878 ElectricAye
879 Kwinn
880 Phil
Page 45
881 Leon
882 TTailspin
883 ElectricAye
884 Jazzed
885 Phil
886 Ravenkallen
887 Mike G
888 Martin H
889 TTailspin
890 Erco
891 Kwinn, bus
892 Kwinn
893 Martin H
894 Mike G
895 Martin H, ram virtual memory
896 Jazzed, tree idea
897 Martin H, physical organization
898 Jazzed, ring tcp/ip layers
899 Mike G
900 Kwinn, tetraprop neural net
Page 46
901 Martin H, neural net ram
902 Leon
903 Phil
904 Erco
905 Duane Degn, continue
906 Jazzed, continue
907 Kwinn
908 The Journey of the Big Brain - Is it the journey or the destination?
909 Improving Neural Injector Data Line Signal Waveforms
910 Merging Technologies - Big Brain with AMD
911 Leon
912 AMD Sources
913 Heater
914 Looking at Speed Ideas
915 Humanoido
916 Dr. Mario, speed
917 Humanoido
918 Dr. Mario, in order out of order technique
918 Out of Order Processing
919 Dr. Mario, out of order, cogs, JITC
920 Dr. Mario
Page 47
921 Mike G
922 Humanoido, GPUs
923 Developing AMD for Parallax Propellers
924 AMD (to Parallax Propeller) Development Boards Source
925 AMD’s Software Kit Source
926 Mike G
927 Humanoido
928 Dr. Mario
929 More about AMD GPUs
930 Mike G
931 Dr. Mario
932 Humanoido
933 Humanoido
934 Dr. Mario
935 Mike G
936 Humanoido
937 Dr. Mario
938 Humanoido
939 Combo Program Era
940 Combo Wiring Era
Page 48
941 Dr. Mario
942 At Once Technology in Large Multi-Prop Machines
943 The Dawning of the Parallel Era
944 Big Brain as a Parallel Machine Is it a monster parallel machine?
945 Introduction of Parallel-Parallel ParP
946 Phil Pilgrim
947 Building a Larger Multiple Point ParP Machine
948 Phil Pilgrim
949 Leon
950 Duane Degn
951 Dr. Mario
952 Dr. Mario, AtOnce At Once discussion
953 Mike G
954 Leon
955 Dr. Mario
956 Mike G
957 Publison
958 Proof of Living Machines
959 Humanoido
960 Multiple Machine Brain Hemispheres
Page 49
961 ElectricAye
962 More on ParaP Parallel-Parallel
963 Dr. Mario
964 Dr. Mario
965 Phil Pilgrim
966 Dr. Mario
967 Phil Pilgrim
968 Parallel-Parallel Universe and the Quantum World
969 Brain Mapping with 3D Extrusion - Transcending Traditional Schematics
970 Mike G
971 Phil Pilgrim
972 2D vs 3D Drawing
973 Humanoido
974 Humanoido
975 Humanoido
976 Ttailspin
977 Mike G
978 Duane Degn
979 Google 3D SketchUp Platform Change
980 Humanoido, Mayan calendar
Page 50
981 Mike G
982 Ttailspin
983 Humanoido
984 ElectricAye
985 Big Brain 3D Mac Sketch Draw Model - 1st discovery wave for analysis
986 Humanoido
987 Arranging Solderless Breadboards
988 Leon
989 ElectricAye, brain convolution
990 Dr. Mario, solderless breadboard arrangement
991 Duane Degn, solderless breadboard
992 Dave Hein
993 Dr. Mario
994 Leon
995 Dr. Mario
996 Leon
997 Breadboards
998 Humanoido
999 Humanoido
1000 Humanoido
Page 51
1001 Breadboard, Aggregate, Partition, Propeller, Expansion, Containment, Var Design
1002 Breadboards 2
1003 Phil Pilgrim
1004 Big Brain's AMD Radeon HD
1005 Big Brain Book - Announcing the beginning of a New Big Brain Book
1006 Brain Interim Test Machine - BIT, Special test machine for Solo and Parallel performance
1007 Dave Hein
1008 Leon
1009 Martin H
1010 Dr. Mario
1011 Leon
1012 Erco
1013 Dr. Mario
1014 Propeller Big Brain' New Computer
1015 Dave Hein
1016 Leon
1017 Big Brain NMRI - Nuclear Magnetic Resonance Imaging Equivalency
1018 Big Brain Goes Robotic - Servo stumps and a mobility platform
1019 Bigger Big Brain Containment Rack - for Brain breadboards now completed
1020 Brain Control & the Robotic Hanger - Mini missions with Brain Copter?
Page 52
1021 Big Brain Living Environment - Air filter and conditioning
1022 ElectricAye
1023 Big Brain Expansion with AMD Radeon HD, High Speed Streaming GPUs
1024 Leon
1025 Earthquake Proofing the Big Brain
1026 Humanoido, quantum definition
1027 Brain Pre Schematic Appearance
1028 Big Brain Loading Computer
1029 ElectricAye
1030 Humanoido
1031 Humanoido
1032 ElectricAye
1033 Phil Pilgrim
1034 BIT Brain Developments - a six Propeller Brain Machine
1035 Jump Over Communications in a Machine Brain
1036 Machine Brain Que Messaging
1037 Merging Propeller Machines - Massive T1 Transposition Machine
1038 Big Brain Collective Assimilation Policy
1039 Mike G
1040 Big Brain June Update - New Mac Computer Setup
Page 53
1041 Big Brain Algorithm Stage
1042 Brain Index Update Addition
1043 MindNode Added to Big Brain - Mind mapping
1044 Guts CAM - Monitor Brain Guts
1045 Mechanical Brains of Yesteryear
1046 Imitation Brain - chemical biological to electrical electronic
1047 Machine Slavery
1048 Robot Brain Chemistry
1049 Brain Image Processing Collective - LinesmART to software collective
1050 Techniques of Brain Image Processing
1051 Propeller Nanite Technology - Introducing the Brain Machine Nanite
1052 Machine Brain Nanite - Timing Nanite made from Spin software
1053 Mike G
1054 Humanoido
1055 Mike G
1056 Humanoido
1057 Mike G
1058 Humanoido
1059 Mike G
1060 Numerical Matrix Analysis Datatrans - New Software Collective: Big Brain Analytical Device
Page 54
1061 3D Medical Imaging & Brain Coronal Slicing - Propeller Machine Big Brain and MRIcroGL
1062 Mike G
1063 Brain Anatomy - Discover the Little Brain - Discovering a second brain in humans and machines
1064 Mini Brain Tutorial - For reference in developing the Machine Brain
1065 Extending Power to Human Brains with Machine Brains
1066 Monthly Propeller Brain Survey
1067 Connecting Machine & Human Brains - Machine Brain sends data to human brain
1068 Connecting Machine & Human Brains - Human Brain sends data to Machine Brain
1069 Convert Your Human Brain Into an Avatar - Journey inside a Propeller Brain may be possible
1070 Updated Brain Index - Added pages 46 through 54
1071 Big Brain Power Tower Containment
1072 Brain Cubed
1073 Big Brain Machine Left & Right Hemispheres
1074 Big Brain Netbook Review
1075 Propeller Brain in a Jar Project - Build A Pint Size Machine Brain
1076 Leon
1077 Humanoido
1078 Big Brain Wonder-Board - New BIg Brain Engineered Building Material
1079 Big Brain Servo Stump - Help decide the the Big Brain Robot Stumps!
1080 Brain Shape Shifting
Page 55
1081 The Amazing No Parts Propeller Machine - When Nothing Has Great Value
1082 Multiple PST Instances
1083 12Blocks with Multiple Props?
1084 Hanno
1085 Hanno
1086 Humanoido
1087 Big Brain Reduction Interface RI
1088 A Smaller 800-Cogger Machine
1089 Instructions on Using a Multi Array ParaP System
1090 Hanno
1091 Humanoido
1092 Duane Degn
1093 Hanno
1094 Humanoido
1095 12 Blocks & Propeller - Front End?
1096 Duane Degn
1097 Hanno
1098 SpotLite Index Propeller & AMD Introducing various SpotLite Indices
1099 Designing a Big Robotic Brain Stub
1100 Duane Degn, dynamixel servo
Page 56
1101 Erco
1102 Duane Degn
1103 Erco
1104 Humanoido
1105 LED Brain Application Chronicles - Part 1 What can it do?
1106 Humanoido
1107 To Simulate or Not To Simulate
1108 Can Your Machine Brain Pass the China Test?
1109 Keeping Tabs On Brain Projects
1110 The Ultimate AI Challenge - the Artificial Brain
1111 Parallel Schematic
1112 Schematic Portfolio
1113 List of Big Brain Schematics - Partial List of Back in Time Schematics
1114 Duane Degn
1115 Humanoido
1116 EEPROM Chip as a Pluggable Memory Device - Plug & Load
1117 Index Update Pages 54, 55, 56
1118 Brain Comparison to JP Morgan Supercomputer
1119 Big Brain EEPROM Schematic - Schematic Portfolio Series
1120 Big Brain Crystal Schematic - Schematic Portfolio Series
Page 57
1121 Big Brain Decoupling Capacitor Schematic - Schematic Portfolio Series
1122 Left Brain Right Brain & AtOnce
1123 Reduce Power Current Consumption - techniques coding the Propeller
1124 Brain Rounds - Where ideas are born
1125 Waveform Noise Filter WNF - Schematic Portfolio Series
1126 Waveform Noise Filter WNF Usage
1127 The Evolution of AtOnce AO Technology
Step by Step development - Understanding the Big Brain
1128 New Paradigm Propeller Big Brain Technology - Connecting brains Man & Machine
1129 Brain Machine Interface
1130 Humanoido
1131 Giant Helping Hydraulic Hand
1132 One/Many Propeller Programmer - Big Brain Applications
1133 Exponential Do-It-Or-Lose-It Development
Big Brain Development Speed Goes Exponential
1134 Tor, google in your head
1135 Big Brain Prop Plug Schematic - Schematic Portfolio Series
1136 Schematic Portfolio Series Development
1137 Leon
1138 Humanoido
1139 The Human to Machine Brain - The Next Generation
1140 ElectricAye
Page 58
1141 Leon, Brain simulation with 1 million ARM cores
1142 Clockless Propeller & Power Reduction
1143 Leon
1144 Mike G
1145 Duane Degn
1146 Impedance Matching
1147 Mike G
1148 Flux Capacitor
1149 Paradigm Beyond Parallel Machine - Propeller Moves Forward
1150 Big Brain Propeller EEPROM Schematic - Schematic Portfolio Series
1151 Big Brain SuperMicroController - Schematic Portfolio Series
1152 Propeller Big Brain Schematic Types - Wiring with Words and Beyond
1153 Big Brain Map History
1154 Throttling the Propeller Clock
1155 Developing an External Oscillator
1156 Brain in a Jar Expanded
1157 Front-Front Mounting - A New Way to Mount Propeller Chips
1158 List of Brain Predecessor Machine Series
Keeping & Maintaining Big Brain Genealogy Records
1159 The Beginning of Brain Milestones
1160 Big Brain Machine Genealogy Series - Update History
Page 59
1161 The BASIC Stump - Robotic Limb for the Big Brain
1162 Robotized EXO - Left Brain Going Robotic - meet Robo EXO!
1163 The BASIC Stump Construction - Side panel design for the Big Brain
1164 Big Brain - Propeller Brain Wave Transfer Machine
1165 1st Brain Wave Monitor - Listening to Propeller Chips
1166 QUAD Brain - Left, Right, Top and Bottom - New Design Implemented
1167 HD Breadboard Production
1168 open for post
1169 Robotic Brain Stem Lost Link
1170 Brain Wave Consideration - Beginning of Neuromachineology
1171 Big Brainwave Cap!
1172 Brain Wave Monitor Sees Big Brain Thoughts
Add a Front End Oscilloscope to see Propeller thinking
1173 DIY Brain Wave Machine - Spotlite Index
1174 mindrobots
1175 prof_braino
1176 jazzed
1177 Humanoido
1178 Machine to Human Brain Interface with Parallax Propellers
1179 Propeller Neural Image Interface Development
Human Brain to Machine Brain
1180 Propeller Neural Image Interface Development
Machine Brain to Human Brain
Page 60
1181 Electromagnetic Injections from a Propeller Machine Brain into a Human Brain
1182 Phil
1183 Multiple Stamps Brain Prop - with Bean's Remarkable BS2Prop
1184 mike g
1185 phil
1186 mike g
1187 kwinn
1188 whit
1189 Persistence of Vision
1190 Building new Brain Wave Monitor BWM - Work begins next version model
1191 Brain Wave Machine Function - Theory of Op
1192 USB Equipment fan - Cooling Overclocked Propellers
1193 Creating Neural Activity in a Propeller Machine Brain - Food for the Brain Wave Machine
1194 Neuron Processors - Renaming Convention
1195 Recording BWM Waves - Squelching the Monster
1196 Propeller Wideband BWM Approach
1197 New Brain Wave Monitor
1198 Propeller Brain Spectral Thought Imprint
Using the new Brain Wave Monitor v2.0
1199 Time Machine for Backups
1200 Propeller Brain Wave Machine - BWM Setup
Page 61
1201 BWM Brain Wave Monitor Characteristics
1202 BWM External Sound Pickup
1203 Brain Wave Sound - The sound of a thinking Propeller brain
1204 BWM Band Exploration
1205 BWM Propeller Suspended Animation
Exploring the Machine Brain with EEG BWM Brain Wave Monitor
1206 Harvesting Brain Voltage
1207 Apple iPhone as a Propeller BWM Recording Device
1208 Propeller Cryogenic Unit - New Lower Cost Method
1209 One Year Anniversary of Big Brain
1210 ElectricAye
1211 Ttailspin
1212 Humanoido
1213 ElectricAye
1214 Humanoido, no condensation with dry ice
1215 One Year Anniversary Party
1216 Humanoido
1217 Backup
1218 Ttailspin, fish tanks
1219 Glass Tank Insulation
1220 The Cerebellation Begins - One year Propeller Big Brain Anniversary celebration
Page 62
1221 Big Brain Index Update P56 through P61 - Updated to post 1219
1222 Updated Big Brain Dictionary
1223 Peltier VS Dry Ice - As a Cryogenic Coolant
1224 Brain Coupler Decoupler
1225 Generating Propeller Brain Square Wave Thought Patterns - Transmit square wave frequencies
1226 Post 1200 Update
1227 Big Brain Thinking Repertoire
1228 Double Parallel
1229 Propeller Brain Spin Speed Test
1230 Natural Computing Progression - for Big Brain expansion representations
1231 Fire Extinguisher as Brain Coolant - Cryogenic Systems
1232 Ttailspin, fire extinguisher precautions
1233 Supercooling Analysis on Solderless Breadboards with Propeller C
Creating Brain Speech Synthesis
Parallax Propeller Takes the Lead as Speech Synthesizer Chip
Adding Speech, TTS Text to Speech, Spelling, Whisper, Singing,
Music, Foreign Language, Lip-Syncing, Up-Chuck...
Breaking News Wednesday February 16, 2011
Introduction to Propeller Speech
Addressing Open Source Options
The Parallax-Propeller Brain has speech! In post 303, we talked about adding speech recognition to the Brain. We're lucky. The Propeller chip alone can do some spectacular speech recognition. Now we turn our attention to gathering information on speech synthesis and text to speech and implementing a working Brain system. The Propeller is equally fully capable of handing the talk. This is so remarkable. The master himself, Chip Gracey, developed the basis of this remarkable capability. In his own words, we've quoted and documented the process he followed to achieve Propeller greatness in terms of speech, including singing. Let's not forget all those that contributed to the cause (mentioned below in more detail) in particular, Phil Pilgrim, for his outstanding contributions. We deeply appreciate these contributions.
Who knew? Perhaps speech was simply hidden in the thousands of Propeller posts or lost in the massive index of the OBEX. But now, for the first time, we've researched the gamut and extracted much of the important and vital detail to get speech and talk up and running on the Brain. This compliments the previous posted methods for speech recognition. Now we have a complete set. No need to think about buying speech chips. You only need a Propeller. This is really big. The Propeller talks! The Propeller listens!
The voice is absolutely fantastic. You'll love the seemingly geared articulated native machine accent and the way you can hone in on the finer aspects of phoneme generation, trimming the formants and adjusting the sound the way you want it. In fact, take a look at the code and you will see the most remarkable control over the voice, and a hoard of improvements and additions, such as whispering, spelling, pauses, inflections, sliding pitch, rolled "r" for foreign language interjections, tempo adjustment, music notation to make songs readable, accents, and considerably more. With this great open source endeavor, Propeller is propelled to the front of the list of chips that do speech processing. Refer to our Propeller Chip Speech Talk Guide below.
In this post we'll examine the other chips and techniques for producing speech in addition to the Propeller chip. It's useful to follow this heritage information and learn more about the foundation and roots of vocal electronic speech synthesis. Note: you'll also want to check out the talking keyboard. We've included links and sources for a lot of related goodies.. Have at it. Talking. Whispering. Listening. Singing. You're guaranteed to have more fun than you imagined!
Who needs a speaker amplifier when you have a spare H-bridge? by Phil Pilgrim http://forums.parallax.com/showthread.php?120420-Who-needs-a-speaker-amplifier-when-you-have-a-spare-H-bridge
Ken sent me an MSR1 controller board with the robot base he built (link) as part of a project he wants me to do. Since the motor-and-wheel units require HB-25s to drive them, the L6205 dual H-bridge onboard the MSR1 was uncommitted. I thought it might be kinda cool if I could press it into service as a speaker amplifier. That way, a speaker could be used with the robot, without any need for external circuitry.
Link: http://forums.parallax.com/showthread.php?p=869245
Why not learn American phonemes? by Loopy Byteloose http://forums.parallax.com/showthread.php?97816-Does-propeller-do-text-to-speech
Why not learn American phonemes?· Just find a dictionary with IPA - internationial phonetic alphabet - to convert to phonemes. IPA is the United Nations standard for all languages of the world. What do you have to know? Roughly there are about 24 Vowel sounds and 24 Consants sounds. The count varies a
bit depending on who does the counting. And in some cases, the sounds are so similar that it is trivial to choose between them - like the two 'th' sounds. In other cases, there are consonant blends - like 'bl', 'fl', etc. add to the inventory. Once you get the hang of it, it has far more control that 'Text-to-speech'. You can even make laughter, a howl or a yodel.· Maybe your chip can sound like a chimpanze. Incidentally, British English requires more phonemes. So American English is likely the easiest start. But please realize that English does allow you to import words from other languages without changes in their sould. That is precisely why text-to-speech never gets it right.Try 'bon voyage', 'pinja colada', 'kreplach', or some other such imported term in your text-to-speech chip.
Loopy Byteloose talks about phonology standards http://forums.parallax.com/showthread.php?126586-Text-to-Speech
Phonology standardization is a rather deceptive topic, not at all simple. Traveling as little as 100 miles reveals regional differences in pronunciation. In fact, efforts of trying to standardized a universal English
pronunciation pretty much have reached absurd levels of debate. Every English dictionary publisher seems to put forth their own system of pronunciation while the United Nations attempts to enforce the rather exotic Universal Phonetic Alphabet (UPA) to encompass all spoken languages of the world. Have you ever heard of "Mid-Atlantic English"? Many people believe it is to become the future of English pronunciation. This is not English pronounced by the the mid-Atlantic states of the USA or any other place on dry land, but is an ideal put forth that is half British and half American as created by the synthesis of rock n' roll between the two countries. And so, rather humorously, they chose to name the dialect for the middle of the Atlantic Ocean. So I suppose that any attempt to create a 'speech chip' would best be supported with an IDE that takes samples from the way people really speak and transfers it to text. But that is only the first hurdle as spelling is idiosyncratic. So you have to create a vast lexicon that associated each word with the proper phonological elements - regardless of variations in spelling. And there in lies the real dilemma - you have to have a search engine stay ahead of the text it is reading and assemble sentences. In some cases, a limited few words can easily be passably spoken. Or idiomatic phrases can be used in a predictable way. But reading whole large texts is not a small microcontroller project. In other words, the project requires handling lots and lots of data. As a teacher of English as a foreign language, it is quite embarrassing to present 'standard pronunciation' while often having difficulty understanding Australians and Englishmen.
Versions
The speech synthesizer for demo board - not Hydra. VIRAND notes: http://forums.parallax.com/showthread.php?114983-text-to-speech-TTS-synthesis
If so, to get it to work, you have to change the crystal in CON to 10_000000 and 8xPLL
You would also have to change the sound pins to 0 and 7 instead of 10 and 11.
If there is a TV object, it too has to be changed to Hydra's pins. as I recall either 58 or %10101 whichever works. I think the wine song added a TV driver and the speech synthesizer doesn't have one.
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad
FOUR MONKS SING 16th CENTURY HYMN INSIDE PROPELLER (in 3.1KB of code)
I've been pretty much holed up for several months working on a vocal tract·object and then a stereo spatializer object. They are both done now. I worked all night to make this demo. Note that·the zip file·contains a new version of the Propeller.exe program which must be used to compile the demo. (The prior·assembler didn't accept RES's as ???_RET label points, but the new one does.)
SingingDemo.zip 810.8 KB http://forums.parallax.com/attachment.php?attachmentid=43861&d=1161986803
From Paul Baker http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page2 http://forums.parallax.com/attachment.php?attachmentid=43872&d=1162053151
Have you listened to the mp3 I posted? Seven is 7 the number, it was his test word for the synth that we heard tens to hundreds of times daily as he worked on the project, so I was joking about it. Spoken and sung is identical except the way the vocal tract is excited. Definition of the speech cookbooks will likely fall upon those Parallax customers who choose to pick up the ball on this. But Chip and/or I will explain the method he used to pick out the required formants for those that want additional words. Seven.mp3.txt
I made one tool
which I've used to "see" what I need to synthesize (formants, and all) by Phil Pilgrim http://forums.parallax.com/showthread.php?p=581578
This program will let you make recordings from your PC microphone and view the resulting audio spectrum in three dimensions: time, frequency, and energy. To see your own voice formants, it helps to make your glottal frequency as low possible by creaking·your voice·and slowly reshaping your mouth to make different vowels. This will tightly space the pitch lines so that the centers of the formants become more prominent. Then, you can point with the mouse and read the center frequency. It's fun!
I modified the testtract application
allows you to fidget with the vocal tract's parameters by Mcstar http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page4
Now it works with Propterminal, so you can use it without a dedicated keyboard or mouse. IF you have propterminal, download this to make it work through your computer's display and keyboard. Also, as an added bonus, I setup some presets for the basic English vowel sounds from the computalk documentation. To access them just hit the function keys f1-f8. Now you have a quick way to jump right to the correct vowel frequencies. Someday I'd like to implement the constanants as well and a buffer so you could type (for instance) "Taek" and have it say "take". Everything is in the Vocal tract to make it possible, just have to work out all the sounds..
Details of Testtract App The Modified Prop Terminal Version
Test tract: A program for fiddling with the variables of Chip's vocal tract object.
By Graham Stabler 5th Nov 06
Modifed by mcstar Aug 8th 2007
Added :
vowels on Function keys F1 - F8
Uses Prop terminal for input and output
Modified :
lowered waits to get faster responses
some presets
Needs PropTerminal!
Reminder from VocalTract.spin:
┌───────────┬──────────────────────┬─────────────┬────────────────────────────────────────────────┐
│ parameter │ description │ unit │ notes │
├───────────┼──────────────────────┼─────────────┼────────────────────────────────────────────────┤
│ aa │ aspiration amplitude │ 0..255 │ breath volume: silent..loud, linear │
│ ga │ glottal amplitude │ 0..255 │ voice volume: silent..loud, linear │
│ gp │ glottal pitch │ 1/48 octave │ voice pitch: 100 ─ 110.00Hz (musical note A2) │
│ vp │ vibrato pitch │ 1/48 octave │ voice vibrato pitch: 48 ─ ± 1/2 octave swing │
│ vr │ vibrato rate │ 0.0763 Hz │ voice vibrato rate: 52 ─ 4 Hz │
│ f1 │ formant1 frequency │ 19.53 Hz │ 1st resonator frequency: 40 ─ 781 Hz │
│ f2 │ formant2 frequency │ 19.53 Hz │ 2nd resonator frequency: 56 ─ 1094 Hz │
│ f3 │ formant3 frequency │ 19.53 Hz │ 3rd resonator frequency: 128 ─ 2500 Hz │
│ f4 │ formant4 frequency │ 19.53 Hz │ 4th resonator frequency: 179 ─ 3496 Hz │
│ na │ nasal amplitude │ 0..255 │ anti-resonator level: off..on, linear │
│ nf │ nasal frequency │ 19.53 Hz │ anti-resonator frequency: 102 ─ 1992 Hz │
│ fa │ frication amplitude │ 0..255 │ white noise volume: silent..loud, linear │
│ ff │ frication frequency │ 39.06 Hz │ white noise frequency: 60 ─ 2344 Hz ("Sh") │
└───────────┴──────────────────────┴─────────────┴────────────────────────────────────────────────┘
See: http://web.inter.nl.net/hcc/davies/esp7cpt.html
'' This program's "say" function accepts a string of bytes that represent English phonemes.
'' It "speaks" them on the port given in the argument to "start". The string can include the following
'' one- and two-character combinations:
''
'' # Select speaker 0.
'' #n Select speaker n (0 =< n =< 9).
'' _ Set the glottal pitch to the base frequency.
'' [ Raise glottal pitch by one semitone.
'' ] Lower glottal pitch by one semitone.
'' / Slide the glottal pitch up by one semitone during the next frame.
'' \ Slide the glottal pitch down by one semitone during the next frame.
'' ' Accent the next frame (same as +\).
'' + Raise the glottal pitch by one semitone. (i.e. "Sharp" the previous note.)
'' +n Raise the glottal pitch by n semitones (n = "1" to "9").
'' - Lower the glottal pitch by one semitone. (i.e. "Flat" the previous note.)
'' -n Lower the glottal pitch by n semitones (n = "1" to "9").
'' A .. G Set the glottal pitch to the indicated note in the current octave.
'' An .. Gn Set the glottal pitch to the indicated note in octave n (n = "0" to "9").
'' % Set the tempo to 100%
'' %nnnn Set the tempo to nnnn% (25 =< nnnn =< 1600) Larger numbers = slower tempo.
'' < Raise the volume by one notch.
'' > Lower the volume by one notch.
'' & Sustain an extra 50mS.
'' &n Sustain an extra n * 10 mS.
'' ~ Add a short "uh" to the end of the last letter (usually a consonant) for emphasis.
'' , Short pause.
'' ; Medium pause.
'' . Long pause.
'' ( Begin whispering.
'' ) End whispering.
'' | Do not interpolate between previous and next phonemes.
'' <blank> Syntactic separator. Prevents adjacent letters from being treated as a pair.
'' a A as in At.
'' ae Long I sound, as in bIte.
'' al AL, as in pAL.
'' ai,ay Long A sound, as in bAIt.
'' ar AR, as in pARt.
'' ah,o "ah" sound, as in pOt.
'' e Short E sound, as in pEt.
'' ee Long E sound, as in fEEd.
'' ew EW, as in pEW.
'' er,ir IR, as in gIRl
'' el EL, as in pELt.
'' i Short I sound, as in hIt.
'' o Short O sound, as in pOt.
'' oa Long O sound, as in bOAt.
'' or OR, as in fORt.
'' ol "ahl" sound, as in mALl
'' ou,ow OU, as in OUt.
'' oi,oy OY, as in bOY.
'' oo Long OO sound, as in bOOt.
'' u Short U sound, as in gUt.
'' uu Short OO sound, as in pUt.
'' d D, as in Dog.
'' dh Soft (voiced) TH sound, as in THat.
'' t T, as in Tot.
'' th Hard (unvoiced) TH sound, as in THink.
'' s S, as in Sip.
'' sh SH, as in SHip.
'' c,k C, as in Cot.
'' ch CH, as in CHip.
'' z Z, as in Zoo.
'' zh ZH sound, as in aZure.
'' l L, as in Lot.
'' r R, as in Rot.
'' rr Rolled R, as in peRRo (Esp.).
'' w W, as in Want.
'' y Y, as in Yell.
'' m M, as in Mom.
'' n N, as in Name.
'' p P, as in Pop.
'' g G, as in Good.
'' b B, as in Bad.
'' f F, as in Fad.
'' h H, as in Had.
'' v V, as in Vat.
'' j J, as in Job.
Other chips, systems, history
eSpeak
open source speech app to review for the english text to phonetic conversion: http://espeak.sourceforge.net/
"Computalker" from 1978 Chip says: A year and a half ago, I found a site that documented a speech synthesizer product called "Computalker" from 1978, which was made by a small company in southern California. It goes into depth about what you have to do, once you have a synthesizer, to make speech sounds. Back then, that synthesizer was necessarily largely analog, but these days, digital silicon has enough horsepower to realize it all in software. Here is the site's url from the Netherlands: http://web.inter.nl.net/hcc/davies/esp7cpt.html
Brain Senses - Focus on Vision Part 1 Color, Light Intensity, Ultrasonics Simple Bee Analogy
Bees are rather complex insects, especially when trying to duplicate all their capabilities with a robot. For example, Bees can seek out color, smell, taste, vision, and touch vibrations. Combine that with path making, dancing, directional navigation, and special roles of reproduction, food generation, protectionism, hive creation, and randomizatiom, and the Bee is a rather complex organism.
Honey bees have been found to distinguish between sweet, sour, bitter and salt, and thus have a sense of "taste." Honey bees use their antennae to gauge the width and depth of cells while constructing comb. They also communicate via touch during bee dances. Bees can see many colors but they do not see red. On the other end of the spectrum, we can't see ultraviolet and honey bees can.
The discussion is how much of a bee's work can we do with a Propeller Brain? Let's break this down into parts.
Color Sensor Parallax offers a Color Sensor for $59.99TCS3200-DB Color Sensor
detect and measure a nearly limitless range of visible colors From Parallax: TCS3200 Color Sensor Daughterboard is a complete color detector, including a TAOS TCS3200 RGB sensor chip, white LEDs, collimator lens, and standoffs to set the optimum sensing distance. It plugs directly into the BASIC Stamp-2pe Motherboard or Propeller Backpack and will also interface to any other BASIC Stamp module or Propeller board using the optional DB-Expander SIP Converter (#28325). The TCS3200-DB can detect and measure a nearly limitless range of visible colors. Applications include test strip reading, sorting by color, ambient light sensing and calibration, and color matching, to name just a few. The TCS3200 has an array of photodetectors, each with either a red, green, or blue filter, or no filter (clear). The filters of each color are distributed evenly throughout the array to eliminate location bias among the colors. Internal to the device is an oscillator which produces a square-wave output whose frequency is proportional to the intensity of the chosen color. Read the documentation below and check out the Color Matching Demo for more detailed information.
TAOS TCS3200 color sensor
Focusable lens: providing a sharply-defined field of view
Two current-regulated white LEDs for illumination
Motherboard connector: compatible with the MoBoStamp-pe, Propeller Backpack, and future Parallax motherboards
ColorPal
Parallax offers the ColorPal for $19.99 miniature color and light sensor
From Parallax: The ColorPAL is a miniature color and light sensor which, through its RGB LED, doubles as a color generator. For sensing color, the ColorPAL uses its LED to illuminate a sample, one color component at a time, along with a broad-spectrum light-to-voltage converter to measure the light reflected back. The amount of light reflected from the sample under illumination from each red, green, and blue LED can be used to determine the sample’s color.The ColorPAL works with non-fluorescent reflective surfaces, preferably those in contact with its light shroud. For a full comparison of the ColorPAL to the TCS3200-DB Color Sensor, please refer to the chart in the ColorPAL documentation.
Detects a full range of colors, and outputs data as RGB (Red/Green/Blue) components.
Detects broad-spectrum ambient light with sensitivity down to 44µW/cm2 per lsb.
Generates 24-bit color using onboard RGB LED.
Plugs into servo headers (with optional cable) or wireless breadboards.
Single-pin interface uses a simple serial protocol to define and initiate color detection and generation.
Color detection and generation details handled by onboard microcontroller.
Onboard EEPROM for saving custom color detection and generation programs.
Autorun feature permits running a pre-designated EEPROM program with only a power supply.
Power requirements: 5.0 VDC
Communication: Serial 1-Wire (asynchronous serial, open drain)
Dimensions: 1.72 x 0.90 x 0.65 in (44 x 23 x 17 mm)
Light to Frequency From ParallaxTSL230R Light to Frequency Converter $5.99 This device will measure light intensity and output a corresponding frequency.
The Texas Advanced Optical Systems (TAOS) TSL230R sensor precisely measures light using an array of photodiodes, with an output of digital square waves. The TSL230R has an input dynamic range of 160dB; that is, it can measure light over a range of 100,000,000-to-1. The TSL230R programmable light-to-frequency converter combines a configurable silicon photodiode and a current-to-frequency converter on single monolithic CMOS integrated circuits. The output can be either a pulse train or a square wave (50% duty cycle) with frequency directly proportional to light intensity. The sensitivity of the device is selectable and the output frequency can be scaled by one of four preset values. An output enable (OE) is provided that places the output in the high-impedance state for multiple-unit sharing of a microcontroller input line.
High-resolution conversion of light intensity to frequency with no external components
Programmable sensitivity and full-scale output frequency
Communicates directly to a BASIC Stamp or SX microcontroller
Absolute output frequency tolerance of +/- 20%
Nonlinearity error (typically 0.2% at 100kHz)
Stable over wide variety of temperatures
Package: 8-pin DIP
Power requirements: 2.7 to 5.5 VDC
Communication: PWM
Dimensions: 0.31 x 0.39 x 0.13 in (7.97 x 9.97 x 3.30 mm)
Operating temp range: -13 to +158 °F (-25 to +70 °C)
Ultrasonics PING))) Ultrasonic Sensor $29.99
Parallax's PING)))™ ultrasonic sensor provides a very low-cost and easy method of distance measurement. This sensor is perfect for any number of applications that require you to perform measurements between moving or stationary objects. Naturally, robotics applications are very popular but you'll also find this product to be useful in security systems or as an infrared replacement if so desired. You will definitely appreciate the activity status LED and the economic use of just one I/O pin. The Ping sensor measures distance using sonar; an ultrasonic (well above human hearing) pulse is transmitted from the unit and distance-to-target is determined by measuring the time required for the echo return. Output from the PING))) sensor is a variable-width pulse that corresponds to the distance to the target. Interfacing to the BASIC Stamp and Javelin Stamp microcontrollers is a snap: a single (shared) I/O pin is use to trigger the Ping sensor and "listen" for the echo return pulse. And the intelligent trigger hold-off allows the PING)))™ to work with the BS1! An onboard three-pin header allows the PING))) to be plugged into a solderless breadboard (on a Boe-Bot, for example), and to be connected to its host through a standard three-pin servo extension cable.
Provides precise, non-contact distance measurements within a 2 cm to 3 m range
Simple pulse in/pulse out communication
Burst indicator LED shows measurement in progress
20 mA power cosumption
Narrow acceptance angle
3-pin header makes it easy to connect using a servo extension cable, no soldering required
Power requirements: +5 VDC
Communication positive TTL pulse
Dimensions: 0.81 x 1.8 x 0.6 in (22 x 46 x 16 mm)
Operating temp range: +32 to +158 °F (0 to +70 °C)
Brain Senses - Focus on Vision Part 2 Image CAM, Object Detection, Infrared
CMUcam CMUcam $139.99 From Parallax: Track images with the Boe-Bot® Robot CMUcam! The Boe-Bot CMUcam ships with printed documentation, CD-ROM with demo programs, and mounting directions. The Boe-Bot CMUcam (#30051) is designed specifically for the Parallax Boe-Bot Robot; allowing the Boe-Bot to find and track colors. Download the complete manual and video at the bottom of the page for more detailed information.
Track user defined color blobs at 17 frames per second, find the centroid of the blob
Gather mean color and variance data Arbitrary image windowing
80x143 resolution
Automatically detect a color and drive a servo to track an object
Slave parallel image processing mode off a single camera bus - advance function
Adjust the camera's image properties - advanced function.
Ability to control 1 servo or have 1 digital I/O pin - advanced function
Power requirements: 4.75 to 5.25 VDC
Communication: Synchronous Serial at 9600 baud
Dimensions: approx. 2.93 x 4.53 x 2.1in (74.4 x 115 x 53 mm)
Operating temp range: -32 to +158 °F (-0 to +70 °C)
The Boe-Bot CMUcam includes a printed user manual, cd-rom with sample code, and a pre-installed custom mounting bracket with two screws. There are other CMUcam kits available which may have different parts, features, and documentation that aren't designed to work specifically with the Boe-Bot robot. The Boe-Bot CMUcam uses the same PCB as the general purpose package (described below) but does not include the parts that convert the serial port to RS232C levels compatible with a PC serial port. It also doesn't include the voltage regulator and jumper headers since they aren't required when using the BASIC Stamp microcontroller. This version can be modified for use with a PC by adding the parts that were left off the board, although the Parallax warranty is voided if you modify the board. While you cannot directly view a picture from the camera on your PC with the Boe-Bot CMUcam setup, a demo program is included that allows you to display the tracking data packets from the CMUcam on the PC debug screen. In some ways this is better than viewing a raw camera picture because you are seeing the data your robot will be using to "see" its world.
A general purpose CMUcam PC evaluation package doesn't include the mounting brackets for the Boe-Bot robot. If you wanted to use this package with the Boe-Bot robot you would need to build a mounting bracket and remove the Max232 chip. Then you would have to add wires from the TTL level serial port to the Boe-Bot robot's BASIC Stamp module. You would also need to add wires to connect the CMUcam to the Boe-Bot robot's battery pack. One potential problem with this is that you can damage the CMUcam or BASIC Stamp module when using the TTL level serial port connection if the power to both is not turned on and off at the same time. The Boe-Bot robot version of the CMUcam can be modified to be the same as the non Boe-Bot robot version of the CMUcam then it will work with the CMU Java program (but voids Parallax warranty).
In order to use the Java PC program the CMUcam needs to operate at 115,200 baud. The Boe-Bot robot version of the CMUcam is strapped to operate at 9600 baud only. You also would need to translate the TTL level serial port to standard RS232C levels for connection to a PC serial port.
Brain Senses - Focus on Vision Part 3 Human Detection PIR Human Detector PIR Sensor $9.99
The PIR (Passive Infra-Red) Sensor is a pyroelectric device that detects motion by measuring changes in
the infrared (heat) levels emitted by surrounding objects. This motion can be detected by checking for a
sudden change in the surrounding IR patterns. When motion is detected the PIR sensor outputs a high
signal on its output pin. This logic signal can be read by a microcontroller or used to drive a transistor to
switch a higher current load. The PIR Sensor detects motion up to 20 feet away by using a Fresnel lens and infrared-sensitive element to detect changing patterns of passive infrared emitted by objects in its vicinity. Inexpensive and easy to use, it's ideal for alarm systems, motion-activated lighting, and holiday props. The PIR Sensor is compatible with all Parallax microcontrollers. BASIC Stamp and SX/B code is available under Downloads below, and Spin code is posted to the Propeller Object Exchange.
Detection range up to 20 feet away
Single bit output
Jumper selects single or continuous trigger output mode
3-pin SIP header ready for breadboard or through-hole projects
Small size makes it easy to conceal
Compatible with BASIC Stamp, Propeller and many other micrcontrollers
Alarm Systems
Holiday animated Props
Motion-activated lighting
Power requirements: 3.3 to 5 VDC
Communication: single bit high/low output
Dimensions: 1.27 x 0.96 x 1.0 in (32.2 x 24.3 x 25.4 mm)
Operating temp range: +32 to +121 °F (0 to +50 °C)
The human brains capacity for learning is HUGE,I heard that if you learned something new every second it would take a trillion years to to fill up the brains capacity.....even if this is not perfectly accurate why would the brain have evolved such a huge capacity for learning if we only live for 70-80 years?
The human brains capacity for learning is HUGE,I heard that if you learned something new every second it would take a trillion years to to fill up the brains capacity.....even if this is not perfectly accurate why would the brain have evolved such a huge capacity for learning if we only live for 70-80 years?
Aaren253, you have an excellent question - the capacity of the human brain may be infinite. Consider that humans generally use 2% capacity and 98% is untapped. Much of this large capacity is based on evolution and characteristics of survival. But what about the imagination, what we call a conscious, and self awareness?
The brain regulates the body which is nerved with massive numbers of sensors, including an autonomic system which functions in the background without our knowledge. The brain is not fully understood. Though it has a finite number of neurons (estimates vary or perhaps brains vary), it's capacity to engage those neurons (in memory for example) far exceeds their numbers, i.e. they have some unknown way of combining and becoming more capable.
The life expectancy you speak of is usually not a limitation of the brain. It is often another part of the body that fails first. Geneticists now believe it will be possible to extend the human life by 200 years in the future with gene technology.
We are still at the beginning of understanding the brain. In the future, it may be possible to non-invasive engage the brain to tap into its knowledge-base for some preservation, even transferal. A lot is riding on the creation and expectations of Artificial Intelligence.
Today, NMR and other neural sensors can interpret brain functions in a fundamental way. Researchers have found a way to create images from our thoughts. Game programmers can use the neural energy of the brain to move virtual objects on a screen.
The human brain is mystery and we simply don't know why it has such great capacity in so many ways.
The complexity of the connectivity between these cells is mind-boggling. Each neuron can make contact with thousands or even tens of thousands of others, via tiny structures called synapses. Our brains form a million new connections for every second of our lives. The pattern and strength of the connections is constantly changing and no two brains are alike. It is in these changing connections that memories are stored, habits learned and personalities shaped, by reinforcing certain patterns of brain activity, and losing others.
Watson - Artificial Intelligence Brain
Wins Jeopardy over humans
Breaking News! http://www.usatoday.com/tech/news/2011-02-17-watson17_ST_N.htm?csp=34news
Watson won decisively after three days against Ken Jennings, left, and Brad Rutter on Jeopardy! Watson, the IBM computer created to be a champ-challenging contestant on Jeopardy!, chewed up and spat out humanity's finest knights of trivia Wednesday night in a $77,147 drubbing of past record winners Ken Jennings ($24,000 total) and Brad Rutter ($21,600).
Fatal Day of Reckoning
So has the fatal day of reckoning arrived, foretold by Frankenstein, 2001: A Space Odyssey and, of course, The Terminator series of man-vs.-machine movies? Even trivia, one of humanity's favorite pursuits, has yielded to the mighty computer.
The Machine
Watson is a Linux system powered by 10 racks of IBM Power 750 servers with 2,880 processor cores. It is capable of operating at 80 teraflops, or 80 trillion floating point operations per second.
The Man
The computing specs of the human brain involve some guesswork, but many estimates, based on the estimated number of neurons and synapses in the brain, put the processing power at about 100 million MIPS, or 100 million million instructions per second. In floating-point terms, estimates have made it 100 petaflops (100 quadrillion flops). Of course, since the brain also is occupied with running the functions of the human body, how many of those flops are focused on the question at hand at any given time is a mystery.
The Technology
Watson technology is designed to answer questions from an internal database that occupies 15 terabytes of memory, or 15 trillion bytes, a byte being the basic unit of memory. IBM figures the Watson technology will find real-world uses besides keeping TV host Alex Trebek company.
Applications
There's health care, helping doctors gather data they need to diagnose and treat disease . There's government service, where Watson could help provide people with information from agencies. In travel, Watson could help tourists with specific information about places they are visiting. And in customer service, Watson could improve online self-service help desks, IBM's material says.
Making Machine Money
Watson may be smart, but it misplayed things by hitting "Jeopardy" first. It could have made a lot more money by starting small and working its way up, beginning with "Wheel of Fortune," then "The Price is Right" and "Deal or No Deal," then "Are You Smarter Than a Fifth-Grader."
Brain Top Down Organization
Organizing Brain modules
The Brain design is now a top down approach.
This indicates, in the vertical orientation, a top
board with various responsibilities. Some of these
elements are activated on the fly while others will be
incorporated full time.
The following initial setup is reviewed:
mouse
keyboard
TV
testing
speech recognition
speech synthesis
At a later date, the developed modules
will be transferred to other boards for more
even distribution of duties. Duties are also
transferred when the chip runs out of resources.
The Brain has an EXOskeleton skin
of composite material consisting of
both inner and outer shrouds.
The Brain already has skin which was recently
transferred to protect and hide the TV when not in use
or required. This skin is black but does not protect
the wiring. Additionally the boards have LEDs and it's
a good idea not to block the visual cues from these
data and programming indicators. Therefore, a new
translucent skin is introduced. This is an outer skin
layer of material that serves these purposes.
protects wring
provides LED visual cues
is almost weightless
All skinning material is from recycled containments
found in China. This is just a fitting. In the final skin,
the unit will extend from top to bottom in sections.
The Inner Brain Skin is the
access cover to the Brain Stomach
The first of two skin types is known as the Inner Skin
and it's a removable section for the TV. This skin
is the "access cover" to the Brain Stomach where
peripheral guts may be hosted or permanently attached.
The Brain Inner Skin snaps into place. No screws,
bolts, nuts or hardware needed. This enables rapid
TV deployment for viewing dreams and data. The black
skin is opaque and made from recycled containments
found in China.
A Parallax Brain TV is made by installing the
TV into the guts of the Brain
The Inner Shoud is removed showing the
location of TV inside the Brain Stomach
Brain TV is important. Its primary functions are:
show thinking
illustrate unfolding dreams
access portal to programming language
brain parametric display
updating stats
a vision eye portal
other sensor view dash
The Brain TV is wedged in between two Protos
and additionally held in place at the base with
a small amount of hot melt glue applied to the
obverse Proto. This allows the TV to continue
with the pivot function for viewing adjustment.
Celebrating The Brain's First Light Unveiling the Brain's 1st functions on TV
In astronomy, new built telescopes celebrate their unveiling by
"First Light," when the instrument has the light of a distant
celestial object, like a star or galaxy, first impinge on its newly
formed optics.
In a similar "light," the Brain was unveiled in "First Light," last
night when the TV display was lit with the first thinking program.
Although simplistic in nature, as first programs may be, it
represents a somewhat historic occasion if you're part of the
Open Source Brain Initiative.
Brain's 1st Light - the first program output to
TV demonstrating the speed at which data can
display. (shown in Vertice Mode)
Keyboard, TV and the green light - all is a "go"
with the Brain! Brain TV is designed as output
for experimenting with this example of
EmbeddedBasic, a language for the Propeller
created by Bean.
Another favorite Propeller language is
FemtoBASIC developed by Mike Green.
Although there are almost 170 programming
languages available for the Propeller, it is
undecided at this time which ones or how
many will be adapted to run on the Brain.
Brain Project Status
Report on the current Brain Project
This is the current view of the Brain project which has
received First Light on Saturday February 18th, 2011.
I am Brain...
The current status of the Brain is
reviewed in this post. Note removal
of the inner skin, outer skin, cryo, and
bus bundle distro so that the inner
portion of the brain is more readily
seen.
The first post in this thread, "Fill the Brain," appeared
August 5th, 2010. It is now one half year later and work
on the Brain has continued throughout the 6-month
duration.
At this time, the Brain has run four languages.
The photo shows the current appearance of the Brain.
While boards are up and running, there is still wiring
that need to be added and completed.
Capabilities continue to increase. In the current state,
the Brain has
Brain Fresnel Tests
Enlarging the image of a Parallax 3.5-inch TV
I'm experimenting with a DIY flat light weight plastic molded 10.5 inch diameter Fresnel lens in front of the 3.5-inch Parallax monitor. It's interesting as tests show it nearly doubles the apparent screen size but at the cost of introducing reflections and some optical aberrations. I plan to do further tests with it. It may be useful with a good mount and a little helpful only if the screen fonts are already legible and tac sharp.
What is a Fresnel Lens? http://science.howstuffworks.com/question244.htm
The thin piece of plastic used here is called a Fresnel lens. It is flat on one side and ridged on the other. Fresnel lenses we first used in the 1800s as the lens that focuses the beam in lighthouse lamps. Plastic Fresnel lenses are used as magnifiers when a thin, light lens is needed. The quality of the image is not nearly as good as that from a continuous glass lens, but in lots of applications (like your RV), perfect image quality is not necessary. The basic idea behind a Fresnel lens is simple. Imagine taking a plastic magnifying glass lens and slicing it into a hundred concentric rings (like the rings of a tree). Each ring is slightly thinner than the next and focuses the light toward the center. Now take each ring, modify it so that it's flat on one side, and make it the same thickness as the others. To retain the rings' ability to focus the light toward the center, the angle of each ring's angled face will be different. Now if you stack all the rings back together, you have a Fresnel lens. You can make the lens extremely large if you like. Large Fresnel lenses are often used as *solar concentrators
Brief History of Fresnel Lenses http://en.wikipedia.org/wiki/Fresnel_lens
A Fresnel lens (pronounced /freɪˈnɛl/fray-NELL) is a type of lens originally developed by FrenchphysicistAugustin-Jean Fresnel for lighthouses. The design allows the construction of lenses of large aperture and short focal length without the mass and volume of material that would be required by a lens of conventional design. Compared to conventional bulky lenses, the Fresnel lens is much thinner, larger, and flatter, and captures more oblique light from a light source, thus allowing lighthouses to be visible over much greater distances.
This before photo shows the Brain with a 3.5-inch TV, too small
to read from a distance
Suddenly the TV Display appears about 75% of the size of a
compared adjacent PC monitor (13.9-inch). The after photo
shows enlargement along with a 20% image degradation and
added reflections
Is the TV screen improved? You can be the judge. Admittedly, the screen can be improved
from this image by moving the lens closer to the TV and decreasing the viewing position.
A shade or darkened room can minimize reflections. Fresnel lenses are not optical coated.
These tests made are with a large Fresnel Lens, size 8 inches by 10.5 inches. Office Fresnel lenses are sold at Office Max for the purpose of magnifying pages from a book. Typical price is about $14.95.
The purpose here is to increase the apparent size of the Brain's tiny display. The TV has a mere 320 x 240 pixels and most 32-character text lines, especially those with half height characters, nearly impossible to work with.
Use of the Fresnel lens does indeed magnify the image. In fact, at a distant viewing angle, the screen can nearly (apparently) double in size. But, does this improve visual quality?
It was found that the lens cannot improve a tiny font that is not tac sharp and and very clear. It can somewhat improve larger fonts that can be read ok without the lens.
The lens is not optical quality. The plastic introduces optical aberrations and reflections. It degrades an image subjectively by approximately 10 or 20%.
In the before and after tests, the enlargement is dramatic. But is the text improved? Look at the photos and you can judge.
Experiments will continue and some ideas for improvements will be implemented. Some improvements are suggested:
Mount the lens
Move the lens a correct distance to minimize aberrations
Tandy Extended Color BASIC has a retro GreenScreen
This brings the total number of languages on the Brain to five. Official install posts will follow respective languages.
PASM
Spin
FemtoBASIC
EmbeddedBASIC
Extended Color BASIC 1.0
To get Extended Color Basic running, I had to modify a statement in the keyboard driver by simply remming out the statement. The statement is identified by the error. The language is running on a Parallax Demo Board located at the Brain Summit. Keep in mind there are 168 possible languages for the Brain. Just how many of these will be installed remains to be seen. Apparently we're looking for BASIC languages that can reside in eeprom and automatically start up at power on.
Here's a quick whip program in Color BASIC to display incrementing screen numbers
10 x=0
20 x=x+1
30 print x;
40 goto 20
run
Data output to screen using
the above program
There's not much information about this version of Color BASIC so I had a look at the Spin code and came up with a small amount of information for a mini-manual.
fb Mini-Manual "it's a fairly functional Tandy Color Computer from 1980!" Chip Gracey
Commands
IF
THEN
INPUT
PRINT
GOTO
GOSUB
RETURN
REM
NEW
LIST
RUN
RND
Boolean Expressions
a < b
a > b
a <> b
a == b
a => b
a =< b
Math functions included
a + b
a - b
b * b
b / b
(others not checked)
Error Reporting
"SYNTAX ERROR", 0
"INVALID LINE NUMBER", 0o
Color Screen Commands Default Green Screen
Command Line Yes
Cursor Yes
Keyboard Yes
TV Yes
Graphics Yes, Graphics Driver v1.0 by Parallax
Points, lines, arcs, sprites, text, and polygons are rasterized into
a specified stretch of memory which serves as a generic bitmap buffer.
The bitmap can be displayed by the TV.SRC or VGA.SRC driver.
See GRAPHICS_DEMO.SRC for usage example.
Chip Gracey Comments
Rokicki, Wow! I wouldn't have believed it if I hadn't run it! For those of you who haven't tried this, it's a fairly functional Tandy Color Computer from 1980! It comes up with a prompt and you can type in programs via keyboard and run them (using the Demo Board). It uses line numbers. I typed in this, and it ran:
10 print "x";
20 goto 10
run
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
I never expected to see something like this, especially so early. Rokicki, I think you must have done this enough times on enough systems that you could do it in your sleep now. I can't think of any other explanation for how you would know WHAT to do so quickly to make a Tandy CC like this. Please note the new efficient VGA character display I posted last night. It will free up almost half the RAM your tv_terminal is using now, plus it's WAY faster. With more memory, you could do way more. I can't believe you even packed in an interpreter!
Of all TV text text drivers tested on the 3.5-inch TV, the best in terms
of readability, sharpness, and clarity is the TV Text Demo v1.0 by
Chip Gracey. This test uses the internal ROM font.
The Brain is running the Propeller TV Text Test by Chip Gracey The driver uses these Propeller fonts for greatest clarity
and visibility, even on the tiny 3.5-inch Parallax TV.
The driver and the demo is in the OBEX Object Exchange. http://obex.parallax.com/objects/67/ This is a derivative of TV Terminal but uses the Propeller’s internal font
and uses much less memory. OBJ and VAR require only 2.8KB.
Brain Wireless Communications System Connecting peripheral robots via wireless interface
One Brain experiment can involve the connection of n-number of Penguin
robots for group swarming, group dancing, and group construction.
Group Construction is when the Brain commands a larger number of
robots to accomplish specific tasks, all working in unison, to assemble
various construction object projects.
Data and commands to and from the Brain are better accomplished with
a wireless interface when remote locations are involved. The Brain will
communicate with peripheral devices. For example, the Brain mouth
and tongue can be located externally and link to the primary Brain functions.
The wireless communication system will use serial programs that can
send and receive data and commands. The idea uses a Parallax #27980
and #27981, transmitter and receiver, to send and receive from the host robots.
The Parallax RF modules provide a very easy and low-cost method of sending data between microcontrollers or to a PC from 500 ft+ line-of-sight (depending on conditions). The receiver unit has a power down feature and a RSSI signal for strength indication. The transmitter unit has a power down feature.
High-speed data transfer rates (1200 ~ 19.2k Baud depending on controller used)
SIP header allows for ease of use with breadboards
Compatible with all BASIC Stamp® modules (including BS1 and Javelin Stamp) and SX chips
As easy to use as simple SEROUT/SERIN PBASIC instructions
Power-down mode for conservative enter usage (longer battery life)
Line-of-sight range of 500 feet (or greater depending on conditions)
Remote Controlled Boe-Bot® robot
Wireless data acquisition
Remote sensors and triggers
Power requirements: 5V +/-10%
Current: ~10 mA normal operation & ~3mA during power down
Date Rate: 12,000 - 19.2 K baud (controller dependent)
Transmission: 500 ft+, based on environment conditions
Dimensions (with antenna): 0.9 x 3.6 in (22.9 x 91.4 mm)
Operating Temperature: -40 to +158 °F (-40 to +70 °C)
Board 23 is a BASIC Stamp Home-
work Board, now added to the
Brain- a green board visible at top
left. This board's function will likely
serve up wireless serial transmissions
and reception to control robots,
peripherals and more remote Brain
components and modules. (seen
here without the transmitter or
receiver)
Today the Brain received a new add-on board mounted near the Summit.
The board has one BS2 processor which is compatible with the Parallax
Transmitter and Receiver.
The Summit location raises the 433mHz antennae to the highest position
in the vertical flip mode for greatest range and least interference. This adds
the real estate of another breadboard for holding the transmitter and
receiver.
Another added aspect of this mounting is the antennae do not need removal in either of the flip positions horizontally and vertically.
The total number of boards is now twenty-three with a varying number of
processors, both in quantity and type.
The board is mounted with two sets of two angle iron connected together
and bolted to the green board.
Spectacular Giant Brain Fly-Through!
Travel through the Brain's Inner space and
document the journey with your Google Camera!
Take a fantastic journey through the inner space of the Brain, exploring three dimensional aspects of thousands of Brain components, defined by Master Google Sketch-Up Artist NikosG.
___________________________________________________________________________________________________________________________________________________
What hidden treasures lurk inside the Brain, deep down in the stomach, or along the inner cavity walls where no has visited from the inside out? For the first time, using computerized CAD, we can take a most fascinating inner Brain journey! Like a Star Wars three dimensional journey, this actual fly-by takes you inside the brain as you whiz by sides of Parallax Propeller boards in this highly detailed view showing thousands of components! The view faces the Brain Summit which is the exit point at the top of the Brain in the vertical Flip Mode. Fly through the Brain and exit out of the Summit, then turn around to skim across the detailed EXOskeleton.
Based on highly accurate three dimensional models provided by master sketcher NikosG of Greece, who first sketched a single Parallax Propeller Proto Board (detailing every hole and socket with added solderless breadboards) and then cloned it twenty one times, this trip takes you where no one has gone before. Twist and turn as you navigate the unseen uncharted interior stomach of the Brain, and zoom along from the inside out!
Brain Project Selects Google 3D SketchUp
Apps developed with free open source 3D package
Brain 3D Image by SketchUp artist NikosG
This view shows the open side of the Brain
which has three boards and mounts two
LCD displays. Not shown is the added TV,
Propeller Demo Board at the top, and a
recently added board also at the top
(a BS2 Homework Board to help dedicate
telecommunications).
Google Sketchup is the 3D choice for illustrating the Brain.
There are numerous aspects to using a 3D model.
Brain On EmbeddedBASIC Adding languages to the Brain
This brain test uses EmbeddedBasic, a language
by Bean with some assistance from Mike Green. In Horizontal Flip mode, the Brain operates as
a console with TV output from EmbeddedBasic.
We are installing various languages into the Brain,
primarily languages that can output to the TV, and
have a keyboard driver. Booting from the eeprom
without intervention is also a feature that's given
priority.
__$WMc%__ writes: I've used EmbeddedBasic on my Propeller Professional Development prototyping board with the key board and a TV driver. Its just like an old TRS-80 but a lot faster. I'm waiting on an SD card reader to continue with this project. I'm using EmbeddedBasic on the Spinneret using Telnet. (see the Spinneret forums for EmbeddedBasic on the Spinneret by Bean)
This is like a remote PC terminal over the INTERNET. EmbeddedBasic (written by Bean and some assistance from Mike Green) is very much like FemtoBasic but it's compiled in PropBasic - PASM instead of Spin, so its much faster than FemtoBasic. Thought this might help your "Brain" project.
It's not loud enough to yell at the neighbors but good enough to give a
beautiful singing performance in a small room made into a concert hall.
The Brain now has a small stereo audio amplifier set in place for voice
speech and singing. Mounting considerations will become a future
project.
A small Chinese Sansui amplifier now replaces headphones in the
Brain so speech and singing is now normally heard across the room
and within group environments, for giving speeches, lecturing, addressing
more than one person and singing performances.
The Sansui amp is used in several ways.
USB powered
Powered by internal rechargeable batteries
Recharged by AC adaper
5Vdc input jack
The unit handles stereo sound input and output with two speakers
approximately 1.75-inch diameter each and two removable plug
cords. The audio and USB cords are each just over 2-feet long. The
model S90 amp has a power switch, bright blue LED power indicator,
power on/off slide switch, and a volume control.
The input cord has a plug compatible with the Parallax Demo Board's
input sound jack and the cord is long enough to reach when the Brain
is in the Vertical Flip Mode.
Currently the Brain Amp, which is 2-inches wide x 6 5/8" long x
1 3/16" deep, is set external to the Brain during use. However, in
another post, details will be given for mounting internally or externally
on the Brain.
Brain Sub-Index - Page 17
Faster sub index gets pasted into the master index
Previous Page 16
301 Propeller Brain Self Education Tutorials for Propeller Programming
302 Brain Searchable Photo Index Nearing completion
303 Brain Speech Recognition Talk to the Brain in your own language
304 New Fast Online Brain Search Index Faster searching without the PDF File
305 Creating Brain Speech - Parallax Propeller Takes the Lead as Speech Synthesizer Chip
306 Brain Senses - Focus on Vision Part 1 Color, Light Intensity, Ultrasonics (6 photos 1 vid)
307 Brain Senses - Focus on Vision Part 2 Image CAM, Object Detection, Infrared (5 photos)
308 Brain Senses - Focus on Vision Part 3 Human Detection (1 photo 1 vid)
309 Brain Capacity Question
310 Brain Capacity Reply
311 NMR Brain Map Neural Map & Interactive Brain Basics
312 Watson - Artificial Intelligence Brain Wins Jeopardy over humans (1 photo)
313 Brain Top Down Organization Organizing Brain modules
314 Brain Outer Skin Protection for wiring (1 photo)
315 Brain Inner Skin Covers TV (1 photo)
316 Installing Brain TV Simple methods to install tv (2 photos)
317 Celebrating The Brain's First Light Unveiling the Brain's 1st functions on TV (2 photos)
318 Brain Project Status Report on the current Brain Project (1 photo)
319 Play Chess Against the Brain Sources for Prop Chess (2 photos)
320 Brain Fresnel Tests Enlarging the image of a Parallax 3.5-inch TV (3 photos) Current Page 17
321 Brain Color BASIC Programming Language - Adding Extended Color BASIC 1.0
322 Brain Text Test Demo
323 Brain Wireless Communications System - Connecting peripheral robots via wireless interface
324 Brain Receives Board 23 - Parallax board serves wireless transmit/receive
325 Spectacular Giant Brain Fly-Through! - Travel through the Brain's Inner space..
326 Brain Project Selects Google 3D SketchUp - Apps developed with free open source 3D package
327 Brain Senses - the Electric Tongue - Focus on Taste
328 Brain On EmbeddedBASIC - Adding languages to the Brain
329 Brain Voice Amplifier - Audio amp supplements headphones
330 Brain Sub-Index - Page 17 - Faster sub index gets pasted into the master index
331 Singing Brain - Brain singing on video with audio track
Singing Brain
Brain singing on video with audio track
The Brain is now singing, as heard in this video's audio
track. What new functions will the Brain learn next? Who
knows?! One one thing is certain, we are the teachers and
the Brain is the student. Nothing to worry about at this
time, unless... the table is turned!
Movie demonstrates a singing brain
It's the smallest resolution video, and sideways, with the sole
purpose of audio to example the singing brain. It uses parts from
the demonstration programs found on the Propeller Parallax
Forum. Note: this is all accomplished with Propeller chips.
Note the fine machine accent and the purity of the tonality
and rhythm. The Spin code has control over the singing
parameters.
Eventually this will be supplemented with new singing
(need Bicycle Built for Two) but for now the goal it to get
everything working..
Comments
Nearing completion
Work is progressing on the new Brain Searchable Photo Index.
Here's a small example of its usefulness. Let's say you're
interested in the position of the small breadboard on the Parallax
Propeller Proto Board. You need photos to position it properly.
Do a PDF search and the following pops up:
PAGE POST
03....49, 50
05....100
06....102, 104
09....163
15....285, 289
Talk to the Brain in your own language
Taking the advice of the original posts about filling the Brain, speech input as the recognition of spoken words will be added to the Brain's repertoire. The propeller is a powerful chip. With hardware from the Parallax Propeller Demo Board (now merged with the Brain Summit), speech input is possible just by adding some software.
Discovery threads
http://forums.parallax.com/showthread.php?129543-Speech-Input
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
Additional speech input thread here
http://forums.parallax.com/showthread.php?100739-Speech-Recognition
There are a number of excellent resources available for the
Propeller chip and other systems
- OBEX 565 by Microcontrolled (Try short burst of continuous spoken speech)
- Goertzel-based speech "recognizer" by Phil Pilgrim (Train any 5 words)
- Speech Recognition by Oldbitcollector (Sample continuous spoken speech)
- Parallax Say-It Module (23 pre-programmed, 32 user definable commands)
- BINARY speech input by Frank DaCosta (speak in Binary language)
and their download links- http://obex.parallax.com/objects/565/
- goertzel_speech - Archive [Date 2009.09.04 Time 16.48].zip
- http://www.machineinteltech.com/index.html
- http://forums.parallax.com/showthread.php?100739-Speech-Recognition
- http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
According to Microcontrolled This program receives voice through the "RecordBase" PUB and then you can record through the "WaitForCommand" PUB and compare it with the previously recorded sample. This object can get it right 50% of the time. Since the command will only work with your (the recorders) voice this is more ideal for security programs then ones needing spoken commands. Mic in circuit is equivalent that of the one on the demo board. Thanks to Jeff Ledger and Raymond Allen for the objects they made that this is based off of.http://obex.parallax.com/objects/565/
Microcontrolled discovery thread
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project/page2
It works by taking your program and replacing the "Play" (although it can be put back in if you want playback, I did that) with a new "CheckRecording" subroutine. It has not only a WAV byte array, but also a "Final" byte array as well. The extra subroutine takes the first part of the "Start" routine from your program and the "Play" subroutine and combines them after the "Record" subroutine call in the "Start" subroutine. It then replaces the playing part of the "Play" routine with a function that checks the sound within a range that is set in the CON block. It reads it byte by byte in decimal mode and then once checked it writes them to temporary VARs. It is doing this in a repeat loop so the temporary VARs get overwritten every time it loops. Anyway it is reading the previous recording and the new recording at the same time, so that is what it is comparing. If it is in the set range (say, "40") then it writes +1 to the globel "sound" VAR. When it is done with this it checks for how consistent it is by guessing how many sound bytes where within range by a value set in the CON block. The value can be 0000 (none right) or 8000 (all right, impossible match) it does the comparison with a "=>" sign so it can be more exact, but not less exact.
Microcontrolled provides a demonstration video
www.youtube.com/watch?v=7X_0wLvo0SQ
Here's the video! It is a bad video camera-wise, when I lean in to the mic to speak I move the camera out of view from the LED's. Has anyone tried it yet? I suggest adjusting the accuracy between 1800 and 4000 if it starts thinking that different words are the original word that was spoken. The thing about it is that it must be initialized. The sound waves must match the speaker's voice. That is what makes it possible to do on the Propeller. Also, the voice samples take about 10k of HUB RAM, however, I could add an SD card and be able to do a 1 time initialization by storing them on the SD card in a WAV file format.
According to Phil
http://forums.parallax.com/showthread.php?115725-Goertzel-based-speech-quot-recognizer-quot-%28now-with-source-code%29
It requires a Propeller demo board and an attached NTSC monitor. That's all. When run, you will be prompted to say the words, "left", "right", "forward", "reverse", and "stop" three times each. Then you will be asked to say any of these words, one at a time. After each utterance, each word will be displayed with three scores, one for each training template, and a decision algorithm will determine which word you said. That's it. Nothing fancy. You can even substitute different words during training, if you like: e.g. their equivalents in another language, say, or the digits "one" through "five". Try it at different microphone distances. It's easiest to watch the monitor if you're not bent over the board speaking directly into the mic. I'm typically leaning back in my chair with the board on the bench. When training it on "right" and "left", try extending the length of your pronunciation, and emphasize the "l" and "r" sounds. That will provide a more detailed template. When testing, every utterance is stretched to fit the template, so the more detailed the template the better. A firend of mine stopped by this afternoon, so I had him try it with templates trained on my voice. It got about 75%, not counting the "say again, please" responses.
According to Oldbitcollector
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
Speech Recognition for the Propeller: Collaborative Project?? After seeing Chip's demo at UPEW I wanted to take his idea to the next level for some simple speech recognition for the Propeller. NOTE: This project is in very early stages! At this point it simply displays the recorded data and plays it back. It is based on Rayman's Parrot player. I'm using Propterminal so I can work in my livingroom. (Included in the zip) You'll need the demoboard with microphone (or equiv) to make this work. I'm looking to "loosely" match high points in the waveform, for simple one word commands. The command "LIGHTS" might turn on an LED.
Speech input method by Dr. Jim (comes with a price and is not open source)
http://www.machineinteltech.com/index.html
Mike Green describes speech recognition
The Prop could do very simple speech recognition. The Apple II had simple speech recognition using a 6502 microprocessor and not a lot of memory. It recorded 8 bit sound in a buffer, normalized it, compressed it, and compared the result to a dictionary of previously recorded compressed sound samples. The accuracy was terrible although a very few carefully chosen words worked well enough for impressive demonstrations.
Mike Green: In the case off BASIC Stamps
Speech recognition is very complex and requires a lot of high speed analysis and the Parallax Stamps are just not suitable for that sort of processing. You would need to use a speech recognition processor and just use the Stamp to control it. One company that makes such a system is www.sensoryinc.com/products/vr_stamp_toolkits.html. Some of the "old" personal computers like the Apple II had simple speech input and pattern analysis programs that would take audio input, normalize it, and count zero crossings to get a measure of the dominant frequency. They would look for silences (to mark the beginning and end of words), then look in a previously processed dictionary to find the best match to the input. These programs would give fair accuracy for a vocabulary of a few words, maybe up to 10-15 words as long as the words were distinctive...
Zoot found a TAB book with a project to develop BINARY speech input
http://forums.parallax.com/showthread.php?100739-Speech-Recognition
name for it "Fredian Grammar" -- for FREquency DIfferential ANalysis.
The book is an old Tab Book -- #1141 -- "How to Build Your Own Working Robot Pet", by Frank DaCosta. Circa 1979. The speaker (you) speaks an arbitrary tone of some loose duration (say anywhere from 1 to 4 seconds). The rough pitch of the tone is measured and set as the "baseline" (in software ONLY for the current run). The 'bot will then expect 4 subsequent "tones", again the durations and spaces are *very* loose. Any tone that is HIGHER in pitch than the baseline is considered binary "1"; any tone lower in pitch than the baseline is binary "0". The 'bot then has your Nibble recognized and decoded. In a sense it's an alternate form of auto-baud-detect serial communication, where the first "start" bit is used to determine the "settings" for the 4 bits to follow. The idea here is that no matter what the speaker's cadences and pitch (a child has a much higher pitched voice) the 'bot will adjust and decode the Nibble. I imagine it would be quite funny to hear in person -- you'd be saying things to your 'bot like "hooooom. ummmm. ahhhh. ahhhh. ummmm" (%0110).
DaCosta implemented his idea nearly 30 years ago. He uses an op-amp and measures the zero-crossing to get a rough pitch. I read the whole chapter and he discards pitches below 160hz and above 1250 hz (but he does his counting and frequency measurements with like 10 dip sockets' worth of latches, shift-registers and 555 timers -- all that could be in firmware). His "ideal" length for the reference and bit pitches is ~ 1 second, with a 1-4 second pause between each. That gives about a 20 second window for receiving the nibble -- if all the bits aren't received within 20 seconds or so, the input is discarded as a bogus transmission. The basic circuit is a crystal mic into a two-transistor buffer which feeds an op-amp for detecting the zero-crossing of the frequency. He chose Nibbles because he says 4 binary "digits" are pretty easy to remember -- going to 6 or 8 bits made it nearly impossible for him to "speak" without a chart. I would tend to agree -- 5-8 bits and you might need a cheat sheet. But given the non-limitations on the firmware, yeah, you could make the "vocabulary" as extensive as your brain could handle.
DaCosta's circuit measures the change -- the first 1 second "tone" received is the threshold. He does a sampling over 2ms and uses that as the "frequency" -- his circuit outputs a square wave TTL from the opamp based on whatever is being received by the mic. Then in software he just uses the count -- if he gets X pulses generated from the original sinusoidal soundwave that's the threshold. Subsequent "tones" are declared "1" or "0" if the count is higher or lower than the threshold.
Speech Input Tips from Beau Schwabe
http://forums.parallax.com/showthread.php?100739-Speech-Recognition
Even if you build a basic one word command vocabulary and just have a few words, there are certain recognizable "patterns" produced depending on the choice of words used. Obviously there will be several words that might have similar patterns that you will want to avoid. Instead of focusing on the actual frequency, focus on the change in frequency (set a threshold and interpret this·as a HIGH or LOW)... sort of like FSK. Also combine this with amplitude patterns. Using just those two speech components might surprise you.
Beau describes another approach Speech Recognition.doc
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
The discussion pjv, Oldbitcollector, and myself had at the EXPO about speech recognition relied more on looking at the integral energy for pattern recognition·more than the frequency of the speech itself.· If you capture the integral energy at specific time intervals,·and compare that to incoming data then the only normalizing that you need to do is adjust for the various rates that the word is spoken at.· This is a fairly simple algorithm to "expand" or "compress" the buffer length before the comparison is made against the stored data.· This method limits some of the words that can be used, i.e. similar words·will have similar energy patterns and can be difficult to distinguish.· But simple word commands will work just fine.
The Demo Board Schematic - Mic Input Sound Circuit Included
http://www.parallax.com/Portals/0/Do...DemoDschem.pdf
Leon describes the technique used on the TRS-80
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project
Low-cost speech recognition system like that which used to be available for use with the TRS-80 were very simple - they used a number of of bandpass filters (implemented with op-amps) with the outputs fed to comparators. The comparator outputs were sampled using an input port, and the samples compared to templates previously created in training sessions. IIRC, it could deal with 32 words. I spent some time playing with the TRS-80 unit and it worked quite well. Something like that could be implemented using an FFT. I keep meaning to try it with a dsPIC, it would be quite trivial.
Capacity according to Hanno
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project/page3
Accurate speech recognition with a large vocabulary isn't here yet- not even with desktop power/memory. However, it should be possible to reliably differentiate between ~10 words with Propeller memory/cpu.
If Speech is too much, you can always resort to clapping your hands..
Finger Snap Commander by OBC fingersnapcommander.spin
http://forums.parallax.com/showthread.php?114219-Speech-Recognition-for-the-Propeller-Collaborative-Project/page6
Detects 1-3 finger snaps (or table knocks) in succession. Not perfect, but it does actually work. Using the microphone on the Demoboard for sampling.
For more recognition words, Parallax'
Say-It Module is available.
http://www.parallax.com/StoreSearchResults/tabid/768/txtSearch/say/List/0/SortField/4/ProductID/589/Default.aspx
Item Code 30080Add voice recognition functionality for 23 built-in pre-programmed or up to 32 user-defined commands. The Say it GUI software for the BASIC Stamp 2 provides an interface for training the module and producing template code. Or, use the robust serial protocol to access the Say It Module functions from other microcontrollers. Currently $59.99
- 23 pre-programmed Speaker Independent (SI) commands
- Up to 32 user definable commands
- SIP header for breadboard friendly projects (0.1" spacing)
- LED and microphone on-board for ease of use
- Creates template programs for the BASIC Stamp 2 in the GUI software
- Power requirements: 3.3 to 5.5 VDC
- Communication: Adjustable Asynchonous Serial (9600 (default), 19200, 38700, 57600, 115200)
- Dimensions: 1.03 x 2.48 x 0.51 in (26.21 x 63.22 x 13.20 mm)
- Operating temp range: +32 to +158 °F (0 to +70 °C)
Downloads & Resources:Say It Documention v1.2 (.pdf)
Say It Software v1.1.5 (.zip)
Say It BS2 Demo (.zip)
Faster searching without the PDF File
I found myself constantly starting up the PDF to search for
specific Brain posts, and this was not the fastest procedure.
The idea came to mind about putting the info in a couple posts
for "search at a glance." The user can still go to EDIT in the
browser and select FIND and search the post to locate content.
It looks like everything fit into one post for homogeneous post
searching.
Page 1
#01 Humanoido: similarity to a human brain, vision processing, memory, autonomic nervous system
#02 P!-Ro: Use an extremely large array of sensors similar to that of the human nervous system.
#03 Leon: Consciousness.
#04 Erco: I would say that all the brainpower in the world needs to be supported by a robot with equally impressive sensors and mechanicals that use all that processing power to move around in and manipulate the world around it.
#05 Whit: keep "out of trouble." That is, keep it from running into things, running off drops or down stairs. keep itself powered, solar panels, calling out for help, trouble alarm. Basic robot safety (protecting itself) would be my first priority. I guess I would aim for the most basic brain functions first.
#06 TinkersALot: Tongue In Cheek Sardonic Grin Smart Aleck anthropocentric thinking human intelligence
#07 Humanoido: autonomic nervous system, react automatically, hot, cold, light, dark, hunger, full, touch, smell, noise, tilt, terrain, wind, hurt
#08 Sylvie369: NYT article link
#09 Humanoido: the brain can be bigger, faster and use more sophisticated AI
#10 Humanoido: Single skill evolution can become evolved, EXPO robots
#11 Lardom: Robot charging station
#12 Humanoido: Determine right from wrong, prioritize
#13 Humanoido: Personality mode
#14 Erco: A sense of duty
#15 P!-Ro: It can vote
#16 Humanoido: interpret the law, a philosophical center
#17 Humanoido: fuzzy logic, less rigid, average, approximate, result inconclusive, gray water, interpret vision, sets of general algorithms apply across the board
#18 Humanoido: snap decisions and judgements when there is limited or no time to think
#19 Humanoido: emotional center, interest heightened or lack, robust behaviors = interesting activities
#20 Humanoido: Transfer information, cog to cog wiring, special brain lobe
Page 2
#21 Humanoido: Thinking faster than original prop specs, internal pure thought should be the fastest
#22 Humanoido: algorithms to transport/understand information/thought, machine approximation
#24 Humanoido: smaller brain, model after the bigger brain, fit hobby budget/resources, go above and beyond the basics, basics include vision, obstacle avoidance, beeping, moving in some patterns, determining location/orientation, sumo, maze solving, wandering, not falling off ledge, ranging, mapping, accepting input from sensors, recharge batteries, beyond basics include thinking, reasoning, ability to resolve problems, accept new challenges
#25 Humanoido: Multi-Brain Concept a duplicate brain, help Alzheimer's, double brain power
#26 Humanoido: (brain in a brain) 2nd brain housed inside the 1st. Though I expect the ability to connect and disconnect brains on the outside would be a useful feature in times of service, debugging or expanding with more brains. Maybe if brains are made inexpensively, they could be discarded and recycled. With multiple brains come dedicated brains. Brains could be located anywhere inside the robot. How about off-the-shelf brains. Companies could compete to see who can make the best brain.
#27 Humanoido: a big brain can be filled with interconnected hybrid processors
#28 Humanoido: A Brain Chart, Brain Stem - route information via nerve center to mobility center
#29 Ratronic: where is the link to the brain chart?
#30 Humanoido: provided link
#31 Humanoido: 1st Hybrid Brain Processor working, 2 languages, 1st successful prototype brain stem
#32 Humanoido: Robotic Brain Stem (with photo)
#33 Humanoido: with photo, Adding the Brain Base to the Big Brain
#34 Humanoido: Robotic Brain Filler
#35 Whit: Please continue posting, very interesting. Don't let the lack of posting discourage you
#36 Humanoido: moved into the next phase which is the actual construction of the brain.
#37 Humanoido: A Working Robot Brain Blob! (with photo)
#38 Humanoido: The Next Brain Blob Addition
#39 Humanoido: Brain Blob Software (Blobber Code)
#40 Humanoido: Open Source
Page 3
#41 Humanoido: Proto Board Brain Surgery Technique to Reduce Power Consumption
#42 Humanoido: Soldering Brain Pins
#43 Jonlink0: action potentials that can be sent are excitatory, and each neuron only has an 8-cell (moore) neighborhood, "waves" of action potentials will grow chaotically from a disturbance in the medium. Some method of creating inhibitory action potentials (perhaps utilizing extra cell states?), as well as input/output methods (easily done by changing certain cell states according to the states of the robot's sensors), may cause interesting behavior. Some sort of inhibitory action potentials are obviously necessary to prevent the automaton from becoming saturated with chaotic activity, which is what Brian's Brain will default to if given semi-random sensor input.
#44 Humanoido: more processors ideal for neural net neuron simulations
#45 Humanoido: software with self reasoning power. It doesn't need to be an Einstein but some intelligence greater than a bug would be appreciated. Memory needs to be added, as so far the sum total is reference eeprom at 20 x 32KRAM. Propeller can access PC and the PC has TeraBytes of operating storage, use a server to provide wireless data storage. Web access can provide a knowledge base to work with.
#46 Humanoido: Brain Guts Data Light Convert Power LED to a Data LED (Parallax Propeller Proto Board)
#47 Humanoido: Brain Definitions as Applied to the Brain Blob The list of Brain components…
#48 Humanoido: Jumper Leads
#49 Humanoido: Brain Span Construction
#50 Humanoido: Brain Blobatory Breadboard Retrofit
#51 Mike G: you do not need a big brain. You need a big network with many specialized processor nodes.
#52 Humanoido: Open Source Project
#53 Humanoido: acting upon information received from some giant server.
#54 Mike G: use one specialized processors for vision, one for hearing, one for voice recognition, and one for speech. Abstracting these tasks makes the whole much more extensible and it allows a device to contain only the nodes needed to fulfill a particular task. Plus it would be easier to place the specialized nodes anywhere on the device.
#55 Humanoido: Brain Blob Preliminary Specs
#56 Mike G: why use a full or half duplex bus over say an 8-bit or 16-bit parallel bus
#57 Humanoido: Brain Stem is using a BASIC Stamp which is capable of doing one thing at one time, full duplex would be meaningless. Half duplex is an ideal match because it's dedicated to motor mobility functions which happen relatively slowly anyway. The Propellers run at full duplex, which do the
upper thinking and higher brain data transfers at higher speeds, hence the hybrid terminology. The master can treat 21 EEPROMs across the slaves as one distributed EEPROM equal to the sum of the individual parts.
#58 Humanoido: Processors tasked out to do specific jobs. Generally in the OBEX we see apps that run in specific cogs. Dedicating cogs/processors to these specific areas of the brain is entirely feasible. The human brain is tasked out in a similar fashion, i.e. a place for vision, motor functions, speech, memory, etc.
#59 Mike G: I can't wrap my mind around the logic it would take to coordinate such memory access
#60 Humanoido: The master can assign indexing to each prop board to define its location which gets stored into eeprom. Slaves and Master can access this global eeprom memory storage location to determine who's who and where they're located. These character maps are drawn out and stored in eeprom, then globally accessed. It's also simple to write a routine to pass variables and store them in specific eeproms. Access is by asking the slave for the information. The IC2 connection is transparently local to any requests and of no global concern.
Page 4
#61 Mike G: I see code executing in a COG on every Prop that deals with bus arbitration and some kind of packet protocol. You'll need a way to process and organize the disparate EEPROM data.
#62 Ravenkallen: develop a weather forecasting module
#63 NikosG: Brain1: Survivability e.g. by returning to a recharging station, or keeping itself in light where it could receive recharging through solar panels or tracking the solar panels (at this point I can contribute) Brain2: Ability to move autonomous and avoid obstacles, and also to choose the best way (Maze problem) Brain4: Ability to take a variety of measurements (use any kind of sensors) (I agree with "Ravenkallen") Brain3: remote communication with it master (ability to send data and receive commands) Brain5: Ability to perform task using a robot arm Brain6: Ability to transform Itself (change shape or leave some mechanical parts in order to achieve something). Have you ever thought your robotic "big Brain" to have a mechanism that can add or remove the aproppriate card in a specific socket?
#64 Humanoido: brain ground based exploration, process telemetry from the probe or satellite
#65 Humanoido: Processing/organizing disparate EEPROMs assigned to master or sub master
#66 Humanoido: legs move, fix things, small hands to reach/grasp, control, perform tasks
#67 Humanoido: tasking interface that could serve as a standard connection point to the outside world
#68 Humanoido: link to USB cable powers Protoboards not over 500mA, for testing and development
#69 Software Overview
#70 Hardware Development
#71 Humanoido: staid algorithms, maze solving, faster, more efficient/sensors, sensors at each side, special sensor - high up telescoping mirror looks at maze top down, ascertain solution differently
#72 Humanoido: shape shifting brain, works with software/hardware, brain carries its own tools/parts,
removing one assembly and attaching another, assemblies store in a spare brain cavity
#73 Mike G: some kind of a bootstapper to "Self Load" code into the multiple Props? Maybe similar to the ZigBee bootloader blog/post?
#74 Humanoido: software currently uses BASIC Stamp commands beginning at the first level of the Brain Stem which filters upwards through the Brain Base and on through the Brain Span
#75 Humanoido: bus single wire, two wire, parallel interfaces, self loading, eeprom, crystal propagation, leave room for future development like the first model T car
#76 NikosG: personal projects with vision, maze, comments
#77 Humanoido: personal projects comments
#78 More about the LED Mod (with photos)
#79 Test Software code used to test the LED modification on the Parallax Propeller Proto Board
#80 Power Regulator Modification (with photo)
Page 5
#81 Humanoido: data light will be installed in as many boards as possible. testing will be a separate project.
#82 Humanoido: follow LED mod installs, decoupling capacitor installation, decoupling capacitor test?
#83 Brain Blob (Dangerous Growth Spurt?) (with photos)
#84 Brain Blob Mods Complete (with photos)
#85 Test Software - Brain Blob Test (with code) BRAIN BLOB TEST.zip
#86 Decoupling Capacitor
#87 Testing Phase
#88 Troubleshooting Phase
#89 MikeG: sorry for the rant
#90 Humanoido: these hobby machines are designed to satisfy my purposes
#91 Troubleshooting Results All boards are Operational
#92 Revised Test Software BRAIN BLOB TESTb.zip
#92 Johlink0: my robot cellular neural network similar to Brian's brain, genetic algorithm to allow learning
#94 Humanoido: The sharing of these ideas will undoubtedly lead to something remarkable.
#95 Software Test 2 brainblobtest2led.spin
#96 Boards on Boards This is the board attachment phase
#97 Power Testing
#98 Testing Conclusions
#99 Micro photo of 241 resistor
#100 Small breadboards are added to PPPBs (photo)
Page 6
#101 Building DIY Breadboards A DIY project for Brain boards (with photos of breadboards)
#102 Testing setup for LEDs using breadboards (photo)
#103 Getting ready to add more breadboards to these PPPBs (photo)
#104 the last PPPB gets a solderless breadboard (photo)
#105 Humanoido: simple examples of learning algorithms, 1 Propeller, apply to multiple processors
#106 Jonlink0: Propeller Life object modify cell-changing algorithm from line 362 onwards
#107 Humanoido: The brain should be able to solve problems in which man never even thought about.
#108 Brain Blob BUS The foundation of the Hybrid BBB (with photos)
#109 Green Brain Blob & Green Guts Approach to recycling hardware and software (with photos)
#110 Brain Cog Power Draw Managing current within a Brain Blob (with illustration)
#111 Brain Work Sheet
#112 All About Brain Serial Interfacing Deciding nature of various connecting interfaces (hookup diagrams)
#113 Resistor Selection Propeller Protection & Pull Down Considerations
#114 Regulator (with hookup diagram)
#115 Barrel Power Connector Basic connections (with PPPB power section illustration)
#116 LED and Surrounding Territory Pictorial Map of LED on PPPB (with illustration)
#117 LED Schematic Sketch for modifying the LED (with illustration)
#118 Connector Pictorial Identifying the Propeller pins on the added connector (with illustration)
#119 PPPB Sketchings & Schematics Useful data notes for hookup (with illustration)
#120 Another Mod to the LED Secondary mod brings power consumption within reason
Page 7
#121 LED Second Mod To bring LED power draw into proper range (with schematic)
#122 LED Resister Determination for 2nd Mod
#123 Introducing Brain Replicants Modular Brain Pieces for Assembly
#124 Humanoido: self repair/maintenance, degradation, dedicated sections, growing memory capacity,
electrical signals, upgrading/evolution, combining components, role in society, function/purpose
#125 Humanoido: a ten year project of reverse engineering the human brain according to this source
#126 Human Brain Map References
#127 post reserved for books on building brains
#128 Pinout of First Connector
#129 Proposed Brain Concepts the current (in flux) brain concept
#130 Important Brain Concepts
#131 Reset Install Examination of method to install reset circuit (with photo)
#132 Basic PPPB with LED Mod Yellow lead from LED resistor to Propeller pin (with photo)
#133 Brain Span Constructed (with photo)
#134 Brain Span Working LEDs indicate functioning (with photo)
#135 Brain Span Troubleshooter Repairs made the next day
#136 Brain Span Animation Showing cycles of two LEDs per board (with animated photo)
#137 Increasing Brain Span Power Reliability Discovering settings to increase reliability
#138 Jumper Data Simplified wiring with jumpers (with photo)
#138 Brain Span Boards Clean Room Kept in dust-free containers (with photo)
#140 Brain Span Test Spin Simple software test for Brain Span brainblobtest3led.spin
Page 8
#141 Brain Span Serial Communications Bspan_send.spin, Bspan_receive.spin (with screen capture)
#142 New Brain Exoskeleton Structure A different kind of Skyscraper (with photo)
#143 Software with BS2 Functions For use with the Brain Blob
#144 Brain Board Configuration Try Out Formulating a final form (with photo)
#145 Nylon Spacers and Hardware Keeping minimal weight
#146 Brain Blob Resistors Revisited Establishing resistor values (with diagram)
#147 Open Season on Serial Objects Serial communications sources abound
#148 Brain Blogging http://forums.parallax.com/entry.php...-Brain-Project
#149 Brain Exoskeleton Redesigned New design improvements
#150 Online LCD Eavesdropping on the Brain's thinking (with photos of LCDs)
#151 Another Question - a Keyboard on your Brain what functions would you assign to each key?
#152 The 1st Propeller Desktop Brain Horizontal Computational Brain Machine (photo)
#153 Whit: Your documentation of this is amazing. I always learn something reading this thread.
#154 Humanoido: hope you can build a brain
#155 Brain Blob and BASIC Stamp Supercomputer Software Similarities are striking
#156 Utilizing Liquid Crystals - the LCD
#157 The Dream World Four types of brain dreaming
#158 Multi-purposed Software
#159 Case of the Missing Software
#160 The EXO: Exoskeleton Physical Form Factor Design Creating a new exo design
Page 9
#161 Connecting EXO Boards Avoiding short circuits (with photo)
#162 Solderless Breadboard Results Favorable results offer permanent solutions
#163 Solderless Breadboard Positioning The critical position is established (with photos)
#164 Dialectric Insulating Strips Design These prevent short circuits (with photo)
#165 Solderless Breadboard Inverted Testing Making sure the breadboards do not disengage
#166 Standard Brain Topology
#167 Time Table New time schedule in effect
#168 Invention of Brain Wrap When parts of your brain stick out (with photos)
#169 Design with Fewer Parts New design is more efficient (with photo)
#170 Optical Illusion One side appears space larger than the other (with photo)
#171 Round Robin Rings Schematic Brain Blob Basic New Design Connections (diagram)
#172 EXO Board Rows Showing the assembly of one EXO side (with photo)
#173 Brain Span Assembly challenge
#174 Right Angle Hardware Selection Angle iron connects Brain Spans together
#175 Balance Focal Point How to balance three brain spans
#176 Brain Span Analysis In terms of weight and wire length (with diagrams)
#177 Brain Span Configuration Making the decision to position weight and wiring (with diagram)
#178 Powering up 5-volt sensors in the Brain
#179 Brain Hybrid Form Factor Establishing a dual form factor brain
#180 Brain Photos Showing Hybrid Exo Configs Days experimenting - various EXO configurations
Page 10
#181 Pyramid Brain - Just for Fun (with photo)
#182 Brain Span Assembly Adjusting the hardware (with photo)
#183 Longer Bolts Create Stubs for Extra Attachments
#184 Getting ready to Program the Brain The 1st version Brain assembly comes into the light (phto)
#185 Brain Slots & Exo Expansion
#186 Brain Secondary Phase Expansion
#187 Injecting & Measuring Power Connector pin header (photo)
#188 Standoff Spacers as Brain Protection Devices spacers protect Brain in desktop modes (photo)
#189 Humanoido: connect human brains, solve brain disease, restore sight, extend human knowledge
#190 Angle Iron for Attaching Host Boards Keeping expansion in mind (photos)
#191 Contemplating Brain Spin-offs Mobility Brain, self modifying hardware, morphing
#192 Self Rewiring Brain A Brain could rewire itself
#193 Brain Card Racks Going with a simple conventional approach (photo)
#194 Brain Boombox Size comparison (photo)
#195 Host Boards Increasing brain capacity (photo)
#196 Brain Span Positioning Important positioning improves interface (photo)
#197 Brain Protection Use of spacers serve multiple purposes (photo)
#198 Brain Dashboard - Vertice Set Utilize vertice for convenient positioning (photo)
#199 Brain Blob Wiring Assembly line wiring of multiple Propeller boards (photo)
#200 Brain Color Coded Wiring Use of color simplifies Brain identifications
Page 11
#201 Brain Wiring Jumpers Establishing wire jumper details
#202 Brain Twin Expansion Using twin Props to expand the Brain (photo)
#203 The Fourth Brain Span Benefit results from creating vertices
#204 Brain New Wiring Concept Sketch brings new ideas for Brain functions
#205 Brain Software Nanites Programmable concept introduces small Brain effectors
#206 Brain Swarms Swarming inside Brains leads to Intelligence
#207 Brain Weigh In How heavy or light is the brain? (photo)
#208 Brains Top Mounting Hardware Brain can host boards at top or sides (photo)
#209 Brain Board Hosting Example shows hosting Brain boards (photo)
#210 Phil Pilgrim: issues
#211 Humanoido: addressing Phil
#212 Brain Thread and Posts Structure
#213 Brain Structural Support Open side receives structural supports (photo)
#214 Brain Feet Increase stability and protection with feet (photo)
#215 Brain Assembly Line Reference Board Increasing the speed and ease of assembly
#216 Brain Class Now you can attend class to learn more about machine learning
#217 Brain Projects Reports on other Brain projects are welcomed
#218 Brain Vertice Defined Showing how to use Vertices (photo)
#219 Brain Reference Board for Assembly Line Use a reference for faster assembly (photo)
#220 Brain Spin Code, Reduce LED Current, small program reduces power consumed by Brain data lights LED_reduction.spin
Page 12
#221 Brain Photo Size Increased photos may appear larger
#222 Brain Logical Addressing Idea for identifying locations (diagram)
#223 Brain Data Light Measurements Setup (micro photo, schematic, photos)
#224 Brain Neighborhood Identification Labels DIY your own Brain Labels (photo)
#225 Power Connectors and Power Test (photos)
#226 Duane Degn: robot navigation, laser scan surrounding, multiProps/cogs analyze, create 3D map, re mobile, switching voltage regulator- they are much more efficient than linear regulators
#227 Humanoido: addressing the wire wrap issue
#228 Brain Address and Identification printed labels for PPPBs (photo)
#229 Humanoido: switching LED power is vastly different
#230 Duane Degn: current & voltage analysis
#231 Power Reduction
#232 Brain Reinforcement Repairing the bent Vertice (photo)
#233 Brain Handles Adjoining spacers double in purpose (photo)
#234 Brain 1st LCD Selected for Output Parallax 4x20 serial LCD (photo)
#235 Brain 4x20 LCD Connection Hardware connects the largest LCD (2 photos)
#236 Brain LCD Spacing not to bump the platform surface during the Brain flipping process (photo)
#237 Brain Large LCD Mod Reversal of hardware facilitates Brain mounting (2 photos)
#238 Brain Nylon Board Connects Connects from board to board use nylon hardware (photo)
#239 Brain Board Insulator and Changes Protecting circuit pathways from short circuits (photo)
#240 Introducing the Flip Brain The flip brain concept for use in any Brain position (5 photos)
Page 13
#241 Two Brain LCDs Intro of 2nd LCD serves multiple purposes (2 photos)
#242 Center Brain Span Reinforcement Center Span flex requires strengthening (2 photos)
#243 Peripheral Adapter Module A platform to hold and attach additional Brain peripherals
#244 Brain Construction - Transparent Plastic Common resource material for construction (photo)
#245 Brain LCD Prepping Small preparation before use (2 photos)
#246 List – projects & products with tiny solderless breadboard
#247 Brain Bagging Bag it - Brain bag your boards for longevity (photo)
#248 Brain Plumbing & Cryogenics Brain installation of piping and routing of service tubes (photo)
#249 Search for Brain Cryogenic Temperature Sensor (6 photos)
#250 Cryogenic Brain Fuels Examination of coolants and effects
#251 Brain Bundle Nerve Distribution (photo)
#252 Brain Hybrid Wiring Establishing a Truth Table for Communications Interfacing (diagram)
#253 Getting Started Brain Phases Checklist 1st Checklist for assembly showing Brain Phases
#254 Brain Schematic Drawing Program Finding a new drawing … (6 photos)
#255 Brain Drawing Program Selection The current choice of programs being explored (2 photos)
#256 Brain Cryo Development Brain Cryo material & removal (photo)
#257 Brain Breather 1 Weekend Brain development Update
#258 Brain Top Mount Real Estate Brain real estate at a premium (photo)
#259 Brain Open Span Board Move Moving a brain board on the open span side (2 photos)
#260 Brain Peripheral Adapter Mount Connecting the mounts (photo)
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#261 Brain LCD Repositioning Improvements to mounting the larger LCD (3 photos)
#262 How to Build a Brain LCD Mount Photos show left and right mount details (3 photos)
#263 Brain Summit Construction of the Brain Summit (3 photos)
#264 Brain 1st Cockpit Outline Cockpit Instrumentation Control Panel Design Ideas
#265 Brain Small LCD Repositioning Increasing Brain board density (2 photos)
#266 Brain Increase in Board Density
#267 Brain Outer Skin Cowling Outer Skin is introduced (photo)
#268 Current Brain Configuration
#269 Brain Summit Board The peak gets a new board! (photo)
#270 Brain Business End Definition of Brain Business End position (photo)
#271 Connecting the Brain Summit Board Hot melt glue is one possibility
#272 Brain Space Telemetry Designs for Telemetry of Brain Cockpit
#273 Duane Degn: project concepts, display, data, boards, communications, loss of spring constant
#274 Humanoido: photo size
#275 Humanoido: response to Duane
#276 The Brain CEO Board Expanding and positioning (photo)
#277 Duane Degn: photo size
#278 Duane Degn: photo beautiful
#279 Humanoido: enlargement in FireFox
#280 Brain Tests - TinyCAD Drawing Program Analysis TinyCAD as Brain drawing program
Page 15
281 Brain Design - Diagram Designer Designs.. Diagram Designer selection & analysis (2 photos)
282 Brain Schematic Elements List of Brain circuit schematic symbols required
283 Schematic Symbols Defined There is no standard so this is a suggested guide (2 photos)
284 Brain Breadboard Virtual Prototyping with Pebble Draw Brain circuits.. (photo)
285 Attaching the Brain Summit Board Hot glue anchors the Summit Board (2 photos)
286 Brain Board Numerical Increase New board total and arrangement
287 Brain Breadboard Virtual Prototyping with Fritzing for BASIC Stamp/Propeller Chips! (photo)
288 Drawing Program Threads For Brain diagram drawing program research
289 Brain's Tiny Breadboard information about the Brain Tiny Breadboard (3 photos)
290 Brain Name Exploring the evolution of the Brain name
291 Brain I/O Ports as Sensors Ideas for I/O - touch sensing and nerve response
292 Brain Search Index Part One Brain thread Index by page, post number, content (photo)
293 Brain Posting Additions Method adds information to previous posts
294 Brain Processor Online/Offline Technique Method alters electronic Brain processors
295 Delegating Brain Components Brain components can reside in 3 places
296 Brain Peripheral Adapter Module Suspended New method speeds up development
297 Brain TV is a Reality Connecting TV via the internal stomach (2 entire brain photos)
298 Electronics & Electrical Tutorials as Brain Resources
299 New Brain Resource Cognition Cognition newsletter directly relates to Brain project (photo)
300 Brain AI News - Supercomputer Plays Jeopardy Machine playing against humans (photo)
Page 16
301 Propeller Brain Self Education Tutorials for Propeller Programming
302 Brain Searchable Photo Index Nearing completion
303 Brain Speech Recognition Talk to the Brain in your own language
304 New Fast Online Brain Search Index Faster searching without the PDF File
305 Creating Brain Speech - Parallax Propeller Takes the Lead as Speech Synthesizer Chip
306 Brain Senses - Focus on Vision Part 1 Color, Light Intensity, Ultrasonics (6 photos 1 vid)
307 Brain Senses - Focus on Vision Part 2 Image CAM, Object Detection, Infrared (5 photos)
308 Brain Senses - Focus on Vision Part 3 Human Detection (1 photo 1 vid)
309 Brain Capacity Question
310 Brain Capacity Reply
311 NMR Brain Map Neural Map & Interactive Brain Basics
312 Watson - Artificial Intelligence Brain Wins Jeopardy over humans (1 photo)
313 Brain Top Down Organization Organizing Brain modules
314 Brain Outer Skin Protection for wiring (1 photo)
315 Brain Inner Skin Covers TV (1 photo)
316 Installing Brain TV Simple methods to install tv (2 photos)
317 Celebrating The Brain's First Light Unveiling the Brain's 1st functions on TV (2 photos)
318 Brain Project Status Report on the current Brain Project (1 photo)
319 Play Chess Against the Brain Sources for Prop Chess (2 photos)
320 Brain Fresnel Tests Enlarging the image of a Parallax 3.5-inch TV (3 photos)
Page 17
321 Brain Color BASIC Programming Language - Adding Extended Color BASIC 1.0
322 Brain Text Test Demo
323 Brain Wireless Communications System - Connecting peripheral robots via wireless interface
324 Brain Receives Board 23 - Parallax board serves wireless transmit/receive
325 Spectacular Giant Brain Fly-Through! - Travel through the Brain's Inner space..
326 Brain Project Selects Google 3D SketchUp - Apps developed with free open source 3D package
327 Brain Senses - the Electric Tongue - Focus on Taste
328 Brain On EmbeddedBASIC - Adding languages to the Brain
329 Brain Voice Amplifier - Audio amp supplements headphones
330 Brain Sub-Index - Page 17 - Faster sub index gets pasted into the master index
331 Singing Brain - Brain singing on video with audio track
332 Opening Up Brain Channels - Brain is capable of multi channels
333 Brain Achieves Cellular Automatronic Life - Propeller Program gives life to the Brain
334 Brain Cellular Automaton Life Options - Screen, algorithm, resolution, cell, evolution
335 Brain Offsetting Technique - Maintaining multi-processing purity
336 Brain Talking Keyboard - Input by hearing the keys
337 Brain Lips - Vocalization sound series
338 Brain Automaton Singing - Beginning of Automatonic Brain Song
339 Teaching the Brain to Count - Regular, Slow & Slow-Fast Counting
340 Sovr: amazing project, working on moods
Page 18
341 Brain Mood 1st Considerations - Psychological state of mind
342 iBrain On LOGO for Unfolding Dream Worlds - Dimensionally Dream with LOGO
343 Brain X-RAY Machine - Developing Brain X-Rays now a Reality
344 Brain TV Tuning for BIG Characters - How to tune a TV driver
345 Brain Thought - Program bouncing in multi cog systems
346 Machine/Human Brain Time Travel - Speed up and slow down brain time
347 Mike G requesting code
348 Humanoido asking if MikeG wants to spend time on it
349 Mike G apologizes
350 Cde use a simulation
351 Humanoid re: code
352 Humanoido re: simulation
353 Brain Base Communications - Design, code, schematics, tests
354 Brain Geneology - From Stamps to Propellers
355 Brain Stem Communications - Revealing Brain Stem test code
356 Brain Appendage Mobility Contemplation
357 Cde simulator, floating point
358 Deriving the Brain Dream Equation - Moving closer to real Propeller dreaming
359 Integer Brain
360 humanoid re: integer, logo
Page 19
361 Cde re: data processing, fixed or float
362 Humanoido re: AI wish list
363 Cde re: need evolutionary software
364 Humanoido re: Six Objectives of Machine Intelligence
365 Prof_Braino re: float is less precise
366 Humanoido re: float etc.,supporting links
367 Six Objectives of Machine Intelligence
368 Prof_Braino re: dreaming is information digestion
369 Prof_Braino re: fixed point calculations
370 Humanoido re: dreaming benefits
371 Humanoido re: collective FP errors
372 The Benefits of Dreaming - The commonality of advanced life forms
373 Six Points of Dreaming - Paving the way towards AI dreaming
374 The Dream of AI
375 Multiple Life Permeation - Fitting life in multiple cogs
376 Brain Monolith Discovery Emergence - The Matrix Monolith emerges from within
377 Brain Dreaming from 2D to 3D - New ELICA LOGO opens up a new realm
378 Propeller Brain Neural Design Moves Forward - The building of neurons
379 doggiedoc (Paul) re: neuroanatomy
380 Humanoido re: cautionary AI (story)
Page 20
381 doggiedoc re: recognition
382 Brain Artificial Intelligence through Gaming - Tic Tac Toe Neural Net
383 Phil re: link showing what 21,000 neurons can accomplish
384 Humanoido re: neurons needed/not needed
385 Martin_H re: california sea slug
386 Phil re: sea slug joke
387 Brain Research - Sea Slugs Computer Modeling
388 Brain Ear 1st Experiments - Mic sound input for analysis
389 Brain Life - Utilize BrainBox Neural Net to Establish Life
390 Brain Progress Report March 2010
391 Brain Dreaming Suggestions - Information Digestion
392 The Problem with Life - Creating expansive Brain life in a non-adiabatic system
393 Ttailspin re: superstitious brain
394 Humanoido re:superstitious brain
395 Brain Superstition in a Neural Starved Life Form - What are the odds with finite Propellers?
396 Brain Breakthrough - a Multi-Propeller Neural Injector (MNI) - Case of the evolving hybrid
397 Brain Matter Injector BMI - Machine injects & distributes neural matter
398 prof_braino re: alarming parts failures
399 Humanoido - Breadboard quality
400 - Brain Neural Fire - Artificial Intelligence Expert System Construct to Mimic Neural Fire using Software
Page 21
401 Brain Self Consciousness - I think therefore I am
402 Brain Turing Test - Fact or Folly?
403 Phil re: cheap parlor trick
404 vaclav_sal re: project suggestions
405 Humanoido re: The AI of ELIZA
406 Phil re: against ELIZA as AI
407 Duane Degn re: book comments, John McCarthy
408 DoggieDoc re: Jeopardy question
409 Mike G re: difficulty of AI, Penrose's "The Emperor's New Mind"
410 Humaoido re: Jeopardy status
411 The Jeopardy Factor
412 The Genius of AI - ELIZA Conversationalist
413 Mike G re: specific tasks quickly with high precision is not AI
414 WHAT IS ARTIFICIAL INTELLIGENCE?
415 AI Conversationalist
416 Duane Degn re: AI
417 Humanoido re: AI sources
418 Big Brain Begat Bantam Brain - Offspring Lineage continues
419 Mike G re questions
420 Brain Transfer & Life Extension - Today's technological levels
Page 22
421 Clever Programming
422 Paul re: washing machines
423 Duane Degn re: humans vs machines
424 Mike G re: a little randomness seems intelligent
425 Mike G re: personal opinion AI and Strong AI
426 Duane Degn re: McCarthy's book
427 Phil re: clever programming is not enough
428 Can a Machine Go Beyond Its Programming?
429 Humanoido re: which book?
430 Mike G re: personal opinion
431 Phil re: personal opinion
432 Humanoido re: posted code, NDA, open source
433 Humanoido re: query
434 Phil re: interrogatives
435 Humanoido re: AI programming details
436 Brain Evolution Programming
437 Humanoido re: washing machine humor
438 Leon re: Penrose subscribes to Hameroff's theory- the brain is a quantum computing system
439 Prof_Braino re: defining the nature of AI
440 Mike G re: AI is what you see in the movies
Page 23
441 Prof_Braino re: What you see in the movies is a cheap McGuffin
442 Mike G re: personal opinion
443 Prof_Braino re: the AI project, Brain etc.
444 A Great Voyage - The uncharted space of brain technology
445 Brain Historical Foundations - Part 1
446 Current Brain States - Small, medium and big
447 Brain Historical Foundations - Part 2
448 Brain Historical Foundations - Part 3
449 Brain Historical Foundations - Part 4
450 SEED to Brain Comparison
451 Twin Brain - 2nd brain twins the first
452 Establishing Neural Brain Power
453 NMI's as Discrete Brains - Neural Matter Injectors are multi-purposed
454 The Establishment of Machine Life
455 Mike G re: There's a lot that goes into opening a door
456 Humanoido re: additions to opening a door
457 Duane Degn re: teaching a robot
458 Brain Neo Cortical Columns
459 Phil re: personal opinion
460 Humanoido re: fractal sources
Page 24
461 Phil re: blocked sites
462 Humanoido re: point is reinforced
463 Phil re: quoting souces
464 Erco re: move on
465 Humanoido: divert resources to better use
466 The new 208 Brain - Another robot Brain is born
467 Brain Matter Folding - Can you fold an electric brain?
468 Phil re: personal opinion
469 Humanoido re: this is an open source hobby (personal use & enjoyment) development
470 Phil re: personal opinion
471 The New Brain 216 - Third Brain Now Under Development
472 Phil re: personal opinion
473 Martin_H re: why do this in hardware?
474 Hardware Software Hybrid
475 Brain Control Panel - Progressing conceptual development
476 New Brain Breadboard Design - Maximize breadboard space used
477 Mike G re: questions
478 More on the Smartest Boe-Bot Project
479 Humanoido re: answers
480 Mike G re: questions
Page 25
481 Humanoido re: answers
482 More on Brain Channeling
483 Humanoido re: answers
484 More about the Neural Matter Injector
485 humanoido re: answers
486 Brain Demo Day - Scientists in China get a glimpse
487 Mike G re: questions
488 Ttailspin re: answers
489 Humanoido re: US40 and Boe-Bot
490 Humanoido re: Brain Channeling
491 Humanoido re: interfacing info
492 Humanoido re: question
493 Mike G re: questions
494 Humanoido re: response
495 Brain Channeling Sources
496 Intro to Interfacing Reconfiguration
497 Humanoido reply to Mike G
498 Humanoido reply to Mike G
499 Humanoido reply to Mike G
500 Prof_Braino comments
Page 26
501 Phil comments
502 Concatenating Brains - Unexpected Brain surplus creates a mammoth Brain!
503 Brain Machine Biology - A symbiotic union of technologies
504 Brain Breaks 100 Processor Chip Barrier! Setting new record, largest Propeller chip machine
505 Brain Propeller Chip Reliability - Parallax Achieves 100% Reliability
506 The Next Generation Brain NGB - A quantum leap of processors
507 A More Manageable Method of Brain Connection
508 Brain Containment - Recycling Appliance Machines
509 Brain LED Array Redesign - New circuit helps offload Propellers
510 Experimenting with the Brain Modular Array
511 Brain Hosting at Max
512 Brain Ultra-Low Power Circuits
513 Brain Multiple Crystal Switching - Simple method for switching test crystals
514 Phil comments
515 Duane Degn comments
516 Humanoido comments
517 Phil comments
518 Mike G comments
519 Brain Crystal Options
520 Mike G comments
Page 27
521 Brain BUS Workings
522 Brain High End Crystal
523 Machine Learning with Lerner - Dave Hein fills a small brain!
524 Mike G comment
525 Humanoido comments
526 Brain Neural Matter Quanta NMQ Defined
527 Brain Neural Matter Quanta NMQ Phase Begins
528 Brain Neuron Output
529 Brain Neuron Quanta Density
530 Concatenation of Propeller NMIs Begins
531 Brain Neuronal Matter Defined
532 Construction of the 1st Brain Machine Neural Device - Making the first neuron
533 The How & Why of Cloning Neurons - Neurons are now being Cloned
534 Ramifications of a Cloned System
535 The many Faces of a Neuron
536 Embedding Machine DNA into the Machine Neuron
537 The Distribution of Neurons in a Machine Brain
538 The Creation of a Synaptic Net in the Brain
539 Machine Brain Synapse Comes Online
540 Second Man-made High Density Board HDB Under Construction
Page 28
541 Big Breakthrough in Machine Brain Technology! - 100,000 Neurons into 1st 100 Propellers
542 Brain Neural Partitioning
543 Neural Net Wiring
544 Neural Injection Design
545 Increasing Neural Net Partitioning
546 Brain Breakthrough! 100,000 Neurons Exceeded - Moving the Giant Brain to the next generation
547 Ttailspin congratulations!
548 Leon questions
549 Humanoido comments
550 Brain Machine Objectives
551 The First Brain Neural Net
552 Phil comment
553 Brain Support Computer is Down
554 Dedicated Brain Support Computer
555 Brain Signal Divide Points
556 DBSC Dedicated Brain Support Computer Selection
557 Brain Signal Divide Point Conditioning
558 Ubrupt Unfortunate Brain Project Termination
559 Martin H use forum & gmail for uploading copies, backups
560 Leon about digital vault backup
Page 29
561 Ttailspin comments
562 Mike G comments
563 Phil uses Knoppix CD
564 Brain Posting & Virus Update
565 Brain Files & Drive Update
566 Phil comments
567 Humanoido comments
568 Functioning of a Complex Machine
569 Phil Knoppix comment
570 Humanoido comment
571 Phil comment
572 Brain Situation
573 Alsowolfman source from scalpel linux to help recover files
574 Brain Computer & Hard Drive Updates
575 Ttailspin comments
576 Humanoido comments
577 Brain Hard Drive Attempted Restoration Update
578 Brain Drive Schedule
579 New Brain Drive Selection
580 The Problem with Backup
Page 30
581 Microsoft Windows is Now Ditched
582 Brain Oriented LINUX & UNIX Training Begins
583 IBM LENOVO ThinkPad Computers Now Trashed
584 Brain's New Computer Selection Nears Finalization
585 Brain is Hermetically Sealed
586 Brain EEPROMs Retain Code
587 Phil comments
588 Martin H humor
589 Humanoido humor
590 Brain Update 04.19.11
591 Brain OS Choices - Examining numerous OS choices
592 Brain Repurposing
593 Developing a New Brain Layering - NB Possible Cancellation
594 Brain Update 04.20.11
595 Brain Layering Computer Design Increase
596 Brain Computer Multipurposing
597 Brain Photos Batch Retrieval
598 "Brain is Back" Campaign
599 New Brain Lab Foundation Announced
600 Working on Brain Wiring
Page 31
601 Ttailspin comments
602 Phil bypass capacitors
603 Brain Posting
604 Big Brain Moving to America
605 Wire Leads Project
606 Mike G questons
607 Humanoido comments
608 Brain HD Update 04.21.11
609 Mike G comments
610 Brains Are Us
611 Brains at the Store - Trip to store has shocking results
612 Brain Computer Could Stall Project
613 PROLOG Added to Brain
614 Building a High Density Brain Breadboard - the solderless kind...
615 Brain New Netbook Stats
616 Ttailspin comments
617 Mike G comments
618 Humanoido comments
619 One Massive Brain Collection - Adding Up Props
620 Mike G comments
Page 32
621 Humanoido comments
622 Mike G comments
623 Brain Drive & Computer Update 04.23.11
624 Phil comments
625 Brain Index Awareness Day
626 Brain Drive & Computer Update 04.23.11b
627 Dave Hein comments
628 Phil comments
629 Humanoido comments
630 Humanoido comments brain index
631 Phil comments
632 Humanoido comments
633 Phil how to link a post number
634 Dave Hein comments
635 Publison comments
636 Humanoido comment post link update
637 Humanoid iphone posting, blog, robotics
638 Humanoido comment
639 Brain Drive & Computer Update 04.25.11
640 Brain Drive & Computer Update 04.26.11 - The Brain's Lost Files
Page 33
641 Remote Brain Posting - Carry your posting "computer" in your shirt pocket
642 Online Brain Index Updated to Page 33
643 Brain Add On Computers - Are they useful?
644 Phil comments Lenovo, T32, WinXP, Mandrake Linux
645 Humanoid commentspc without CDs
646 Stats on the Restored Hard Drive - the Brain Wins! Almost nothing is restored
647 Schematic Request Related to Brain Development
648 Phil comments how to retrieve attachments
649 Humanoido comments
650 Apple AMD Radeon HD 6750M Graphics Card 480 Stream Processors
651 Brain Gets Apple Mac Computer
652 Stepping up the Big Brain
653 Brain Config in April
654 Brain Config in May
655 Brain Programming Languages Selection SPIN, OPENCL, PBASIC, PASM, XCODE
656 Brain Relegated to ProMac Symbiotic Union
657 New Ideas for Autonomous Brain Backup - Cloning from Backup
658 Robotic Brain Mobility & Robotics
659 Zoot comments trademarks
660 Brain Naming Conventions
Page 34
661 Big Brain Design Breakthroughs with PROPELLERS & MACS
662 Big Brain Gains Utilizing Hard Drives
663 Big Brain's Supplanted Memory
664 Brain Programming in XCode 4
665 *** Change in Brain Project Development ***
666 Phil comments less stream of consciousness
667 Duane Degn comments
668 Mike G comments you're working on the cutting edge
669 Brain Project Overview - Props and computers
670 Humanoido comment
671 Humanoido comment celebration
672 Phil comments incredulous
673 Dave Hein comments be patient Phil
674 Is Brain DNA Genome Possible?
675 Brain Life Power Challenges & Considerations
676 Big Brain Genome Maps Instead of Schematics
677 Parallax-Propeller-Equipped Brain Genetic Machine Genome Project
678 Big Brain Sex - Is the Big Brain Hermaphrodite, Male or Female?
679 Humanoido comments grasshopper
680 Big Brain Propeller Waves - Different clocks for different blocks
Page 35
681 Build a Big Brain Propeller Qualitative EEG Machine - Measure Big Brain's Brain Waves
682 Big Brain EEG Machine as a Diagnostic
683 Leon comments neuron example to solve xor problem
684 Big Brain State of the INIT-Neuron
685 Phil comments
686 Leon comments ANN, Hull University, MSc project, Dataglove, BAe, MAD, Brough
687 Humanoido comments
688 Mike G comments asking for neuron code
689 Leon comments Here is a neural net toolbox for Scilab
690 Humanoido comments not posting code
691 Links to Managed Neural Projects
692 Mike G comments
693 humanoid comments no posting of development or test code for the reasons cited
694 Dave Hein comments you have expressed a lot of good ideas
695 Humanoido comments Brain development or documenting partial Brain development
696 Jazzed Tetra Prop Spins Brain Life Ideas
697 Dave Hein comments on posting code
698 Duane Degn comments on his great projects!
699 Brain Methodology
700 Humanoid comments to Dave Hein
Page 36
701 Potential of Connecting the Degn Massive LED Array
702 Future Brains with Afflictions - The 1st Guide to Machine Intelligence Sickness
703 Duane Degn comments about LED Array
704 Machine Brain Neurons and Neural Matter - New Brain Dictionary Definitions
705 Refinement Brain's Hybrid Interface - Successful Sharing Hybrid results in fewer wires
706 Brain Neural Complexity - Adding to the Brain Dictionary
707 Dictionary of Propeller Machine Brain Terms
708 Big Brain's Hyper Neural Threading HNT
709 Big Brain Domain Partition - Propeller DPs increase volume performance
710 Propeller Brain Change with Supporting Computers
711 Leon comments TFLOPS
712 What is the Giant Brain? Propeller or Other?
713 Leon comments simulate the ANN on the Mac
714 The Propeller ANN Mac
715 Propeller Brain Mac GPUs Selected
716 Many Faces of the Giant Propeller Brain
717 Moving Toward Ultra Brain with Props & Macs
718 Giant Brain TFLOPS
719 Leon comments 5,000 I/Os
720 Big Brain Backup Terabyte Drives
Page 37
721 Massive Propeller Brain Trinary State Output Device - a plane with quadrillions...
722 Brain Merging with the Massive Transposition Machine
723 Big Brain BOSS - Brain Operating Software System
724 Brain Doctor Meeting 05.14.11
725 AI Quotations
726 ElectricAye comments Kurzweil, Chinese Room
727 Humanoido comments Chinese Room
728 New Type of Propeller Simplex Neuron SN - Modified INTNeuron and Test Neurons? (with pseudo code)
729 Phil comments problem with early AI research, top down, bottom up
730 Reverse Engineering Evolution
731 Giant Machine Brain Eats Propellers
732 Little Parts - a Machine in the Machine - Isolate your brains
733 ElectricAye comments
734 Dave Hein comments modeling nerve cells
735 Phil comments cannot simulate intelligence without considering environmental factors
736 Leon comments consciousness
737 Phil comments unique possession of consciousness
738 Leon comments qualia
739 Time Stamping Human Evolution
740 Humanoid comments human consciousness and pure thought
Page 38
741 Mike G comments neurons, simple neural net
742 Defining Consciousness
743 ElectricAye comments
744 Exploring the Neural Net with the Simplex Neuron
745 Phil comments code
746 Programming to be Self Aware
747 Humanoido comments intention is to release BOSS when it reaches BETA
748 Controlling the Brain with Light
749 Mike G comments neurons
750 Simplex Neurons
751 Phil comments
752 Humanoido comments to Phil
753 Big Brain Self Rewiring
754 BST and Mac
755 Mike G comments neuron memory
756 Mike G comments neuron memory
757 Handling Neurons
758 NEURAL BRAIN MAP
759 Mike G comments neuron memorny
760 Phil comments source code
Page 39
761 Brain Map Revisions
762 Mike G comments on muffler wiring
763 Brain History & Challenges - Historical roots, humanoids, multi-processing machines
764 Humanoido comments car forum
765 Mike G comments
766 Determining Memory Usage
767 The Uphill Computer Journey
768 Mike G comments neuron memory
769 Humanoid comments neuron size matters
770 Mike G comments
771 Humanodo comments
772 Phil comments
773 Humanoido comments
774 Big Brain Index Update
775 Mike G neuron like spin code
776 Phil comments
777 Humanoido comments
778 Humanoido comments
779 The Big Brain Propeller Neural Map
780 TeraByte Propeller Brain Drives Arrive
Page 40
781 Big Brain Mirrors - No Glass
782 Big Brain Self Awareness - Making the Machine Big Brain Self Aware
783 Dave Hein comments on self aware
784 Doggidoc Paul comments on self aware
785 Self Awareness Early in Life
786 Humanoido comments to Dave Hein about Learner
787 Dave Hein comments about Lerner
788 Phil comment about Lerner
789 Humanoido comment about Lerner
790 Dave Hein comment about Lerner
791 humanoido comment about Lerner
792 Brain Child - More about the begotten brain child
793 Principle Parts of the Brain
794 Setting Standards of a Big Brain - First Intro of Functions
795 Zoot comments spelling
796 Humanoido comments spelling
797 Brain Gastropod Locomotion
798 Brain Mobility Through Snailing
799 Robots in a Brave New World Need a Brain
800 Brain Parts - the Next Level
Page 41
801 Big Brain in June
802 Baby Brain - Child Brain Leads to Baby Brain
803 Big Brain on the Multiple Props Projects List
804 ElectricAye
805 Brain Chip Independence Day - Neural Matter Independence and benefits
806 Humanoido
807 Automatic Brain Repair by Optical Illusion - Can a Machine Brain repair itself?
808 Big Brain to Increase Vision Processing Speed
809 Perceptions in Machine Vision - Arrow left or arrow right?
810 Ttailspin
811 Duane Degn
812 Doggidoc
813 Humanoido
814 Erco
815 Humanoido
816 Propeller Brain Subdomain Test Segmenting - Creating a subDomain
817 Big Brain Evil, Scary & Sarcastic Sides?
818 Big Brain Peripheral Enumeration - Six pin Enumeration
819 Brain Enumeration & subEnumeration
820 Intro to Propeller Big Brain Fluid
Page 42
821 Dave Hein, the illusion
822 Phil
823 Humanoido
824 Phil
825 Humanoido
826 Enumeration Schematic - 6 pin method with two lines
827 Dave Hein, using 4 pins tertiary
828 Trinary Enumeration - Using the float/limbo state
829 Brain Speed Doodle
830 Phil
831 Humanoido
832 Constructing a Transparent Plastic Brain Base - For Child & Baby Brains
833 Jazzed, another brain collage
834 Humanoido
835 Brain Travel Voltage Tip
836 The Magical Brain Partition - Big Brain will loan his chips to others
837 Big Brain Goes On the Multi-Prop List
838 ElectricAye
839 Jazzed, Turing test
840 Leon, take over the world
Page 43
841 Ttailspin
842 Jazzed, nothing wrong with art
843 Mike G, impressive work
844 Jazzed, turing test
845 Mike G
846 Jazzed
847 Phil
848 Jazzed
849 ElectricAye, Turing test
850 Jazzed
851 Mike G
852 Jazzed
853 Propeller Neural Net Conception
854 Ttailspin
855 Humanoido, machine deception not required
856 Jazzed
857 Phil
858 Humanoido
859 Jazzed
860 Ttailspin
Page 44
861 Jazzed, links
862 Publison
863 Robotic Big Brain
864 Humanoido, Lerner
865 Jazzed
866 Humanoido
867 Humanoido
868 Jazzed
869 Martin H, upload code as backup
870 Phil
871 ElectricAye
872 Jazzed
873 Phil
874 Leon
875 Martin H, neural net skepticism
876 Mike G
877 Ttailspin
878 ElectricAye
879 Kwinn
880 Phil
Page 45
881 Leon
882 TTailspin
883 ElectricAye
884 Jazzed
885 Phil
886 Ravenkallen
887 Mike G
888 Martin H
889 TTailspin
890 Erco
891 Kwinn, bus
892 Kwinn
893 Martin H
894 Mike G
895 Martin H, ram virtual memory
896 Jazzed, tree idea
897 Martin H, physical organization
898 Jazzed, ring tcp/ip layers
899 Mike G
900 Kwinn, tetraprop neural net
Page 46
901 Martin H, neural net ram
902 Leon
903 Phil
904 Erco
905 Duane Degn, continue
906 Jazzed, continue
907 Kwinn
908 The Journey of the Big Brain - Is it the journey or the destination?
909 Improving Neural Injector Data Line Signal Waveforms
910 Merging Technologies - Big Brain with AMD
911 Leon
912 AMD Sources
913 Heater
914 Looking at Speed Ideas
915 Humanoido
916 Dr. Mario, speed
917 Humanoido
918 Dr. Mario, in order out of order technique
918 Out of Order Processing
919 Dr. Mario, out of order, cogs, JITC
920 Dr. Mario
Page 47
921 Mike G
922 Humanoido, GPUs
923 Developing AMD for Parallax Propellers
924 AMD (to Parallax Propeller) Development Boards Source
925 AMD’s Software Kit Source
926 Mike G
927 Humanoido
928 Dr. Mario
929 More about AMD GPUs
930 Mike G
931 Dr. Mario
932 Humanoido
933 Humanoido
934 Dr. Mario
935 Mike G
936 Humanoido
937 Dr. Mario
938 Humanoido
939 Combo Program Era
940 Combo Wiring Era
Page 48
941 Dr. Mario
942 At Once Technology in Large Multi-Prop Machines
943 The Dawning of the Parallel Era
944 Big Brain as a Parallel Machine Is it a monster parallel machine?
945 Introduction of Parallel-Parallel ParP
946 Phil Pilgrim
947 Building a Larger Multiple Point ParP Machine
948 Phil Pilgrim
949 Leon
950 Duane Degn
951 Dr. Mario
952 Dr. Mario, AtOnce At Once discussion
953 Mike G
954 Leon
955 Dr. Mario
956 Mike G
957 Publison
958 Proof of Living Machines
959 Humanoido
960 Multiple Machine Brain Hemispheres
Page 49
961 ElectricAye
962 More on ParaP Parallel-Parallel
963 Dr. Mario
964 Dr. Mario
965 Phil Pilgrim
966 Dr. Mario
967 Phil Pilgrim
968 Parallel-Parallel Universe and the Quantum World
969 Brain Mapping with 3D Extrusion - Transcending Traditional Schematics
970 Mike G
971 Phil Pilgrim
972 2D vs 3D Drawing
973 Humanoido
974 Humanoido
975 Humanoido
976 Ttailspin
977 Mike G
978 Duane Degn
979 Google 3D SketchUp Platform Change
980 Humanoido, Mayan calendar
Page 50
981 Mike G
982 Ttailspin
983 Humanoido
984 ElectricAye
985 Big Brain 3D Mac Sketch Draw Model - 1st discovery wave for analysis
986 Humanoido
987 Arranging Solderless Breadboards
988 Leon
989 ElectricAye, brain convolution
990 Dr. Mario, solderless breadboard arrangement
991 Duane Degn, solderless breadboard
992 Dave Hein
993 Dr. Mario
994 Leon
995 Dr. Mario
996 Leon
997 Breadboards
998 Humanoido
999 Humanoido
1000 Humanoido
Page 51
1001 Breadboard, Aggregate, Partition, Propeller, Expansion, Containment, Var Design
1002 Breadboards 2
1003 Phil Pilgrim
1004 Big Brain's AMD Radeon HD
1005 Big Brain Book - Announcing the beginning of a New Big Brain Book
1006 Brain Interim Test Machine - BIT, Special test machine for Solo and Parallel performance
1007 Dave Hein
1008 Leon
1009 Martin H
1010 Dr. Mario
1011 Leon
1012 Erco
1013 Dr. Mario
1014 Propeller Big Brain' New Computer
1015 Dave Hein
1016 Leon
1017 Big Brain NMRI - Nuclear Magnetic Resonance Imaging Equivalency
1018 Big Brain Goes Robotic - Servo stumps and a mobility platform
1019 Bigger Big Brain Containment Rack - for Brain breadboards now completed
1020 Brain Control & the Robotic Hanger - Mini missions with Brain Copter?
Page 52
1021 Big Brain Living Environment - Air filter and conditioning
1022 ElectricAye
1023 Big Brain Expansion with AMD Radeon HD, High Speed Streaming GPUs
1024 Leon
1025 Earthquake Proofing the Big Brain
1026 Humanoido, quantum definition
1027 Brain Pre Schematic Appearance
1028 Big Brain Loading Computer
1029 ElectricAye
1030 Humanoido
1031 Humanoido
1032 ElectricAye
1033 Phil Pilgrim
1034 BIT Brain Developments - a six Propeller Brain Machine
1035 Jump Over Communications in a Machine Brain
1036 Machine Brain Que Messaging
1037 Merging Propeller Machines - Massive T1 Transposition Machine
1038 Big Brain Collective Assimilation Policy
1039 Mike G
1040 Big Brain June Update - New Mac Computer Setup
Page 53
1041 Big Brain Algorithm Stage
1042 Brain Index Update Addition
1043 MindNode Added to Big Brain - Mind mapping
1044 Guts CAM - Monitor Brain Guts
1045 Mechanical Brains of Yesteryear
1046 Imitation Brain - chemical biological to electrical electronic
1047 Machine Slavery
1048 Robot Brain Chemistry
1049 Brain Image Processing Collective - LinesmART to software collective
1050 Techniques of Brain Image Processing
1051 Propeller Nanite Technology - Introducing the Brain Machine Nanite
1052 Machine Brain Nanite - Timing Nanite made from Spin software
1053 Mike G
1054 Humanoido
1055 Mike G
1056 Humanoido
1057 Mike G
1058 Humanoido
1059 Mike G
1060 Numerical Matrix Analysis Datatrans - New Software Collective: Big Brain Analytical Device
Page 54
1061 3D Medical Imaging & Brain Coronal Slicing - Propeller Machine Big Brain and MRIcroGL
1062 Mike G
1063 Brain Anatomy - Discover the Little Brain - Discovering a second brain in humans and machines
1064 Mini Brain Tutorial - For reference in developing the Machine Brain
1065 Extending Power to Human Brains with Machine Brains
1066 Monthly Propeller Brain Survey
1067 Connecting Machine & Human Brains - Machine Brain sends data to human brain
1068 Connecting Machine & Human Brains - Human Brain sends data to Machine Brain
1069 Convert Your Human Brain Into an Avatar - Journey inside a Propeller Brain may be possible
1070 Updated Brain Index - Added pages 46 through 54
1071 Big Brain Power Tower Containment
1072 Brain Cubed
1073 Big Brain Machine Left & Right Hemispheres
1074 Big Brain Netbook Review
1075 Propeller Brain in a Jar Project - Build A Pint Size Machine Brain
1076 Leon
1077 Humanoido
1078 Big Brain Wonder-Board - New BIg Brain Engineered Building Material
1079 Big Brain Servo Stump - Help decide the the Big Brain Robot Stumps!
1080 Brain Shape Shifting
Page 55
1081 The Amazing No Parts Propeller Machine - When Nothing Has Great Value
1082 Multiple PST Instances
1083 12Blocks with Multiple Props?
1084 Hanno
1085 Hanno
1086 Humanoido
1087 Big Brain Reduction Interface RI
1088 A Smaller 800-Cogger Machine
1089 Instructions on Using a Multi Array ParaP System
1090 Hanno
1091 Humanoido
1092 Duane Degn
1093 Hanno
1094 Humanoido
1095 12 Blocks & Propeller - Front End?
1096 Duane Degn
1097 Hanno
1098 SpotLite Index Propeller & AMD Introducing various SpotLite Indices
1099 Designing a Big Robotic Brain Stub
1100 Duane Degn, dynamixel servo
Page 56
1101 Erco
1102 Duane Degn
1103 Erco
1104 Humanoido
1105 LED Brain Application Chronicles - Part 1 What can it do?
1106 Humanoido
1107 To Simulate or Not To Simulate
1108 Can Your Machine Brain Pass the China Test?
1109 Keeping Tabs On Brain Projects
1110 The Ultimate AI Challenge - the Artificial Brain
1111 Parallel Schematic
1112 Schematic Portfolio
1113 List of Big Brain Schematics - Partial List of Back in Time Schematics
1114 Duane Degn
1115 Humanoido
1116 EEPROM Chip as a Pluggable Memory Device - Plug & Load
1117 Index Update Pages 54, 55, 56
1118 Brain Comparison to JP Morgan Supercomputer
1119 Big Brain EEPROM Schematic - Schematic Portfolio Series
1120 Big Brain Crystal Schematic - Schematic Portfolio Series
Page 57
1121 Big Brain Decoupling Capacitor Schematic - Schematic Portfolio Series
1122 Left Brain Right Brain & AtOnce
1123 Reduce Power Current Consumption - techniques coding the Propeller
1124 Brain Rounds - Where ideas are born
1125 Waveform Noise Filter WNF - Schematic Portfolio Series
1126 Waveform Noise Filter WNF Usage
1127 The Evolution of AtOnce AO Technology
Step by Step development - Understanding the Big Brain
1128 New Paradigm Propeller Big Brain Technology - Connecting brains Man & Machine
1129 Brain Machine Interface
1130 Humanoido
1131 Giant Helping Hydraulic Hand
1132 One/Many Propeller Programmer - Big Brain Applications
1133 Exponential Do-It-Or-Lose-It Development
Big Brain Development Speed Goes Exponential
1134 Tor, google in your head
1135 Big Brain Prop Plug Schematic - Schematic Portfolio Series
1136 Schematic Portfolio Series Development
1137 Leon
1138 Humanoido
1139 The Human to Machine Brain - The Next Generation
1140 ElectricAye
Page 58
1141 Leon, Brain simulation with 1 million ARM cores
1142 Clockless Propeller & Power Reduction
1143 Leon
1144 Mike G
1145 Duane Degn
1146 Impedance Matching
1147 Mike G
1148 Flux Capacitor
1149 Paradigm Beyond Parallel Machine - Propeller Moves Forward
1150 Big Brain Propeller EEPROM Schematic - Schematic Portfolio Series
1151 Big Brain SuperMicroController - Schematic Portfolio Series
1152 Propeller Big Brain Schematic Types - Wiring with Words and Beyond
1153 Big Brain Map History
1154 Throttling the Propeller Clock
1155 Developing an External Oscillator
1156 Brain in a Jar Expanded
1157 Front-Front Mounting - A New Way to Mount Propeller Chips
1158 List of Brain Predecessor Machine Series
Keeping & Maintaining Big Brain Genealogy Records
1159 The Beginning of Brain Milestones
1160 Big Brain Machine Genealogy Series - Update History
Page 59
1161 The BASIC Stump - Robotic Limb for the Big Brain
1162 Robotized EXO - Left Brain Going Robotic - meet Robo EXO!
1163 The BASIC Stump Construction - Side panel design for the Big Brain
1164 Big Brain - Propeller Brain Wave Transfer Machine
1165 1st Brain Wave Monitor - Listening to Propeller Chips
1166 QUAD Brain - Left, Right, Top and Bottom - New Design Implemented
1167 HD Breadboard Production
1168 open for post
1169 Robotic Brain Stem Lost Link
1170 Brain Wave Consideration - Beginning of Neuromachineology
1171 Big Brainwave Cap!
1172 Brain Wave Monitor Sees Big Brain Thoughts
Add a Front End Oscilloscope to see Propeller thinking
1173 DIY Brain Wave Machine - Spotlite Index
1174 mindrobots
1175 prof_braino
1176 jazzed
1177 Humanoido
1178 Machine to Human Brain Interface with Parallax Propellers
1179 Propeller Neural Image Interface Development
Human Brain to Machine Brain
1180 Propeller Neural Image Interface Development
Machine Brain to Human Brain
Page 60
1181 Electromagnetic Injections from a Propeller Machine Brain into a Human Brain
1182 Phil
1183 Multiple Stamps Brain Prop - with Bean's Remarkable BS2Prop
1184 mike g
1185 phil
1186 mike g
1187 kwinn
1188 whit
1189 Persistence of Vision
1190 Building new Brain Wave Monitor BWM - Work begins next version model
1191 Brain Wave Machine Function - Theory of Op
1192 USB Equipment fan - Cooling Overclocked Propellers
1193 Creating Neural Activity in a Propeller Machine Brain - Food for the Brain Wave Machine
1194 Neuron Processors - Renaming Convention
1195 Recording BWM Waves - Squelching the Monster
1196 Propeller Wideband BWM Approach
1197 New Brain Wave Monitor
1198 Propeller Brain Spectral Thought Imprint
Using the new Brain Wave Monitor v2.0
1199 Time Machine for Backups
1200 Propeller Brain Wave Machine - BWM Setup
Page 61
1201 BWM Brain Wave Monitor Characteristics
1202 BWM External Sound Pickup
1203 Brain Wave Sound - The sound of a thinking Propeller brain
1204 BWM Band Exploration
1205 BWM Propeller Suspended Animation
Exploring the Machine Brain with EEG BWM Brain Wave Monitor
1206 Harvesting Brain Voltage
1207 Apple iPhone as a Propeller BWM Recording Device
1208 Propeller Cryogenic Unit - New Lower Cost Method
1209 One Year Anniversary of Big Brain
1210 ElectricAye
1211 Ttailspin
1212 Humanoido
1213 ElectricAye
1214 Humanoido, no condensation with dry ice
1215 One Year Anniversary Party
1216 Humanoido
1217 Backup
1218 Ttailspin, fish tanks
1219 Glass Tank Insulation
1220 The Cerebellation Begins - One year Propeller Big Brain Anniversary celebration
Page 62
1221 Big Brain Index Update P56 through P61 - Updated to post 1219
1222 Updated Big Brain Dictionary
1223 Peltier VS Dry Ice - As a Cryogenic Coolant
1224 Brain Coupler Decoupler
1225 Generating Propeller Brain Square Wave Thought Patterns - Transmit square wave frequencies
1226 Post 1200 Update
1227 Big Brain Thinking Repertoire
1228 Double Parallel
1229 Propeller Brain Spin Speed Test
1230 Natural Computing Progression - for Big Brain expansion representations
1231 Fire Extinguisher as Brain Coolant - Cryogenic Systems
1232 Ttailspin, fire extinguisher precautions
1233 Supercooling Analysis on Solderless Breadboards with Propeller C
Parallax Propeller Takes the Lead as Speech Synthesizer Chip
Adding Speech, TTS Text to Speech, Spelling, Whisper, Singing,
Music, Foreign Language, Lip-Syncing, Up-Chuck...
Breaking News Wednesday February 16, 2011
Introduction to Propeller Speech
Addressing Open Source Options
The Parallax-Propeller Brain has speech! In post 303, we talked about adding speech recognition to the Brain. We're lucky. The Propeller chip alone can do some spectacular speech recognition. Now we turn our attention to gathering information on speech synthesis and text to speech and implementing a working Brain system. The Propeller is equally fully capable of handing the talk. This is so remarkable. The master himself, Chip Gracey, developed the basis of this remarkable capability. In his own words, we've quoted and documented the process he followed to achieve Propeller greatness in terms of speech, including singing. Let's not forget all those that contributed to the cause (mentioned below in more detail) in particular, Phil Pilgrim, for his outstanding contributions. We deeply appreciate these contributions.
Who knew? Perhaps speech was simply hidden in the thousands of Propeller posts or lost in the massive index of the OBEX. But now, for the first time, we've researched the gamut and extracted much of the important and vital detail to get speech and talk up and running on the Brain. This compliments the previous posted methods for speech recognition. Now we have a complete set. No need to think about buying speech chips. You only need a Propeller. This is really big. The Propeller talks! The Propeller listens!
The voice is absolutely fantastic. You'll love the seemingly geared articulated native machine accent and the way you can hone in on the finer aspects of phoneme generation, trimming the formants and adjusting the sound the way you want it. In fact, take a look at the code and you will see the most remarkable control over the voice, and a hoard of improvements and additions, such as whispering, spelling, pauses, inflections, sliding pitch, rolled "r" for foreign language interjections, tempo adjustment, music notation to make songs readable, accents, and considerably more. With this great open source endeavor, Propeller is propelled to the front of the list of chips that do speech processing. Refer to our Propeller Chip Speech Talk Guide below.
In this post we'll examine the other chips and techniques for producing speech in addition to the Propeller chip. It's useful to follow this heritage information and learn more about the foundation and roots of vocal electronic speech synthesis. Note: you'll also want to check out the talking keyboard. We've included links and sources for a lot of related goodies.. Have at it. Talking. Whispering. Listening. Singing. You're guaranteed to have more fun than you imagined!
Development of Propeller Speech & Code Resources
Phonemic Speech Synthesis
Companion to Goertzel-based Speech Recognizer
(3rd installment, 7 Nov 2006) by Phil Pilgrim
http://forums.parallax.com/showthread.php?89411-Phonemic-Speech-Synthesis-%283rd-installment-7-Nov-2006%29&p=613308
http://forums.parallax.com/showthread.php?89411-Phonemic-Speech-Synthesis-%283rd-installment-7-Nov-2006%29
The Companion to Phonemic Speech Synthesis
Goertzel-based speech "recognizer" by Phil Pilgrim
http://forums.parallax.com/showthread.php?115725
talk_demo - Archive [Date 2006.10.31 Time 23.55].zip
talk_demo - Archive [Date 2006.11.04 Time 19.18].zip
talk_demo - Archive [Date 2006.11.07 Time 22.15].zip
http://forums.parallax.com/attachment.php?attachmentid=43928&d=1162398261
http://forums.parallax.com/attachment.php?attachmentid=44013&d=1162726079
http://forums.parallax.com/attachment.php?attachmentid=44052&d=1162995843
Phil's thread on his Talk object with downloads
http://forums.parallax.com/showthread.php?p=613308
Chip Gracey This represents a lot of hard-won knowledge that's taken me years to accumulate. It's been one of the most fascinating endeavorsof my life. I hope a few of you out there will get some enjoyment from this. If you are interested enough to spend a few hours delving into the zip below, reading the documentation, running the examples, and doing some experimentation of your own, you may get·the bug, yourself, work on Speech synthesis using formants..
http://forums.parallax.com/showthread.php?114012-Speech-Synthesis-on-the-Propeller
http://forums.parallax.com/attachment.php?attachmentid=62908&d=1250244623
Chip's Propeller vocal tract simulator
This object synthesizes a human vocal tract in real-time. It requires one cog and at least 80 MHz.
http://obex.parallax.com/objects/72/
Propeller Speech Synthesis.zip
http://forums.parallax.com/attachment.php?attachmentid=61888&d=1246261602
Simple recursive executor in Spin by Chip Gracey
very data-efficient - VocalData.spin
http://forums.parallax.com/attachment.php?attachmentid=61890&d=1246278487
PhiPi's phoneme to vocal tract parameter translator works as a front end
http://forums.parallax.com/attachment.php?attachmentid=74680&d=1287954659
talk_demo update 4.zip
Text to Speech
Text to speech at Gadget Gangster site by NickMcClick
http://forums.parallax.com/showthread.php?126217-Looking-for-feedback-on-Propeller-Getting-Started-
http://www.gadgetgangster.com/sell-your-project/324
using objects to do text-to-speech
Text To Speech thread by Agent440
http://forums.parallax.com/showthread.php?115165-Text-To-Speech
Add a set of Lips
Voice Synthesis with Lip-syncing by Phil Pilgrim
http://forums.parallax.com/showthread.php?110102-Voice-Synthesis-with-Lip-syncing
Code Additions, Extensions
Mctrivia's code: talking numbers using Phils talk demo
http://forums.parallax.com/showthread.php?121737-Speech-synth
PUB sayNumber(uiNum) case uiNum 0 : oT.say(string("oa~klok")) 1 : oT.say(string("wun~")) 2 : oT.say(string("too")) 3 : oT.say(string("three")) 4 : oT.say(string("for")) 5 : oT.say(string("faev")) 6 : oT.say(string("siks")) 7 : oT.say(string("s'even~")) 8 : oT.say(string("ayt")) 9 : oT.say(string("naen~")) 10: oT.say(string("ten~")) 11: oT.say(string("el'even~")) 12: oT.say(string("twelv~")) 13: oT.say(string("th'irteen~")) 14: oT.say(string("f'orteen~")) 15: oT.say(string("f'ifteen~")) 16: oT.say(string("s'iksteen~")) 17: oT.say(string("s'eventeen~")) 18: oT.say(string("'aytteen~")) 19: oT.say(string("n'aenteen~")) 20: oT.say(string("tw'entee")) 30: oT.say(string("th'irtee")) 40: oT.say(string("f'ortee")) 50: oT.say(string("f'iftee")) other: sayNumber((uiNum/10)*10) sayNumber(uiNum//10)Information Section
Chip Gracey giving a talk/demo on speech synthesis with the Propeller
http://www.parallax.com/Portals/0/Downloads/mm/video/upew/Chip%20Gracey%20-%20Speech%20Synthesis%20(long).wmv
check out Chapter-12 documentation that Chip worked on
http://forums.parallax.com/showthread.php?p=830898
Info on computerized phonetics, spectral analysis software
http://www.fon.hum.uva.nl/praat/
Novel Amplifier for Speech
Who needs a speaker amplifier when you have a spare H-bridge? by Phil Pilgrim
http://forums.parallax.com/showthread.php?120420-Who-needs-a-speaker-amplifier-when-you-have-a-spare-H-bridge
Ken sent me an MSR1 controller board with the robot base he built (link) as part of a project he wants me to do. Since the motor-and-wheel units require HB-25s to drive them, the L6205 dual H-bridge onboard the MSR1 was uncommitted. I thought it might be kinda cool if I could press it into service as a speaker amplifier. That way, a speaker could be used with the robot, without any need for external circuitry.
Link: http://forums.parallax.com/showthread.php?p=869245
Basic Up-Chuck
Make your Propeller sick by Chip Gracey
http://forums.parallax.com/showthread.php?87036-Propeller-gonna-hurl
SpinSick.spin
http://forums.parallax.com/attachment.php?attachmentid=42548&d=1153384046
Discussions
Why not learn American phonemes? by Loopy Byteloose
http://forums.parallax.com/showthread.php?97816-Does-propeller-do-text-to-speech
Why not learn American phonemes?· Just find a dictionary with IPA - internationial phonetic alphabet - to convert to phonemes. IPA is the United Nations standard for all languages of the world. What do you have to know? Roughly there are about 24 Vowel sounds and 24 Consants sounds. The count varies a
bit depending on who does the counting. And in some cases, the sounds are so similar that it is trivial to choose between them - like the two 'th' sounds. In other cases, there are consonant blends - like 'bl', 'fl', etc. add to the inventory. Once you get the hang of it, it has far more control that 'Text-to-speech'. You can even make laughter, a howl or a yodel.· Maybe your chip can sound like a chimpanze. Incidentally, British English requires more phonemes. So American English is likely the easiest start. But please realize that English does allow you to import words from other languages without changes in their sould. That is precisely why text-to-speech never gets it right.Try 'bon voyage', 'pinja colada', 'kreplach', or some other such imported term in your text-to-speech chip.
Loopy Byteloose talks about phonology standards
http://forums.parallax.com/showthread.php?126586-Text-to-Speech
Phonology standardization is a rather deceptive topic, not at all simple. Traveling as little as 100 miles reveals regional differences in pronunciation. In fact, efforts of trying to standardized a universal English
pronunciation pretty much have reached absurd levels of debate. Every English dictionary publisher seems to put forth their own system of pronunciation while the United Nations attempts to enforce the rather exotic Universal Phonetic Alphabet (UPA) to encompass all spoken languages of the world. Have you ever heard of "Mid-Atlantic English"? Many people believe it is to become the future of English pronunciation. This is not English pronounced by the the mid-Atlantic states of the USA or any other place on dry land, but is an ideal put forth that is half British and half American as created by the synthesis of rock n' roll between the two countries. And so, rather humorously, they chose to name the dialect for the middle of the Atlantic Ocean. So I suppose that any attempt to create a 'speech chip' would best be supported with an IDE that takes samples from the way people really speak and transfers it to text. But that is only the first hurdle as spelling is idiosyncratic. So you have to create a vast lexicon that associated each word with the proper phonological elements - regardless of variations in spelling. And there in lies the real dilemma - you have to have a search engine stay ahead of the text it is reading and assemble sentences. In some cases, a limited few words can easily be passably spoken. Or idiomatic phrases can be used in a predictable way. But reading whole large texts is not a small microcontroller project. In other words, the project requires handling lots and lots of data. As a teacher of English as a foreign language, it is quite embarrassing to present 'standard pronunciation' while often having difficulty understanding Australians and Englishmen.
Versions
The speech synthesizer for demo board - not Hydra. VIRAND notes:
http://forums.parallax.com/showthread.php?114983-text-to-speech-TTS-synthesis
If so, to get it to work, you have to change the crystal in CON to 10_000000 and 8xPLL
You would also have to change the sound pins to 0 and 7 instead of 10 and 11.
If there is a TV object, it too has to be changed to Hydra's pins. as I recall either 58 or %10101 whichever works. I think the wine song added a TV driver and the speech synthesizer doesn't have one.
Errors
Fix the error
http://forums.parallax.com/showthread.php?109375-Vocal-Tract-sine-error
every time I try to compile the VocalTract object I get an error on line 326 saying "Expected a DAT symbol."the line says "call #sine" Answer: Download the latest Propeller Tool. A change was made in the compiler a while back to allow a label like sine_ret to be a 'res'. Or, you can change that 'call #sine' to 'jmpret sine_ret,#sine'. Note: thanks installing 1.2(http://www.parallax.com/Portals/0/Downloads/sw/propeller/Setup-Propeller-Tool-v1.2.exe) fixed it.
Applications
Fantastic App for people physically requiring speech
http://forums.parallax.com/showthread.php?90547-One-for-Chip-Speech-synthesis
Make your Propeller Sing!
Singing monk squad by Chip Gracey
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad
FOUR MONKS SING 16th CENTURY HYMN INSIDE PROPELLER (in 3.1KB of code)
I've been pretty much holed up for several months working on a vocal tract·object and then a stereo spatializer object. They are both done now. I worked all night to make this demo. Note that·the zip file·contains a new version of the Propeller.exe program which must be used to compile the demo. (The prior·assembler didn't accept RES's as ???_RET label points, but the new one does.)
SingingDemo.zip 810.8 KB
http://forums.parallax.com/attachment.php?attachmentid=43861&d=1161986803
From Paul Baker
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page2
http://forums.parallax.com/attachment.php?attachmentid=43872&d=1162053151
Have you listened to the mp3 I posted? Seven is 7 the number, it was his test word for the synth that we heard tens to hundreds of times daily as he worked on the project, so I was joking about it. Spoken and sung is identical except the way the vocal tract is excited. Definition of the speech cookbooks will likely fall upon those Parallax customers who choose to pick up the ball on this. But Chip and/or I will explain the method he used to pick out the required formants for those that want additional words. Seven.mp3.txt
Chip says: it sounds like Pachelbel's Canon
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page2
Because the timing got hosed up due to the increase in frames per tract per note, it wound up playing the four parts, basso to soprano, in sequence for every note period. Now it sounds like Pachelbel's Canon:
http://forums.parallax.com/attachment.php?attachmentid=43871&d=1162051163
MP3 file of the singing monks from MikeGreen
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad
You have to download it, then rename it by removing the ".txt" extension so it's just ".mp3". Then it should play with any MP3 player. File Type: txt PropellerMonks.mp3.txt
http://forums.parallax.com/attachment.php?attachmentid=43862&d=1162005716
Developments, Accomplishments, Refinements
I made one tool
which I've used to "see" what I need to synthesize (formants, and all) by Phil Pilgrim
http://forums.parallax.com/showthread.php?p=581578
This program will let you make recordings from your PC microphone and view the resulting audio spectrum in three dimensions: time, frequency, and energy. To see your own voice formants, it helps to make your glottal frequency as low possible by creaking·your voice·and slowly reshaping your mouth to make different vowels. This will tightly space the pitch lines so that the centers of the formants become more prominent. Then, you can point with the mouse and read the center frequency. It's fun!
I've made a program for TV and keyboard
so you can fiddle with the parameters and see the effects by Graham Stabler
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page3
Might be handy for tweaking. testtract.spin
http://forums.parallax.com/attachment.php?attachmentid=44011&d=1162718509
I modified the testtract application
allows you to fidget with the vocal tract's parameters by Mcstar
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page4
Now it works with Propterminal, so you can use it without a dedicated keyboard or mouse. IF you have propterminal, download this to make it work through your computer's display and keyboard. Also, as an added bonus, I setup some presets for the basic English vowel sounds from the computalk documentation. To access them just hit the function keys f1-f8. Now you have a quick way to jump right to the correct vowel frequencies. Someday I'd like to implement the constanants as well and a buffer so you could type (for instance) "Taek" and have it say "take". Everything is in the Vocal tract to make it possible, just have to work out all the sounds..
Details of Testtract App
The Modified Prop Terminal Version
Test tract: A program for fiddling with the variables of Chip's vocal tract object. By Graham Stabler 5th Nov 06 Modifed by mcstar Aug 8th 2007 Added : vowels on Function keys F1 - F8 Uses Prop terminal for input and output Modified : lowered waits to get faster responses some presets Needs PropTerminal! Reminder from VocalTract.spin: ┌───────────┬──────────────────────┬─────────────┬────────────────────────────────────────────────┐ │ parameter │ description │ unit │ notes │ ├───────────┼──────────────────────┼─────────────┼────────────────────────────────────────────────┤ │ aa │ aspiration amplitude │ 0..255 │ breath volume: silent..loud, linear │ │ ga │ glottal amplitude │ 0..255 │ voice volume: silent..loud, linear │ │ gp │ glottal pitch │ 1/48 octave │ voice pitch: 100 ─ 110.00Hz (musical note A2) │ │ vp │ vibrato pitch │ 1/48 octave │ voice vibrato pitch: 48 ─ ± 1/2 octave swing │ │ vr │ vibrato rate │ 0.0763 Hz │ voice vibrato rate: 52 ─ 4 Hz │ │ f1 │ formant1 frequency │ 19.53 Hz │ 1st resonator frequency: 40 ─ 781 Hz │ │ f2 │ formant2 frequency │ 19.53 Hz │ 2nd resonator frequency: 56 ─ 1094 Hz │ │ f3 │ formant3 frequency │ 19.53 Hz │ 3rd resonator frequency: 128 ─ 2500 Hz │ │ f4 │ formant4 frequency │ 19.53 Hz │ 4th resonator frequency: 179 ─ 3496 Hz │ │ na │ nasal amplitude │ 0..255 │ anti-resonator level: off..on, linear │ │ nf │ nasal frequency │ 19.53 Hz │ anti-resonator frequency: 102 ─ 1992 Hz │ │ fa │ frication amplitude │ 0..255 │ white noise volume: silent..loud, linear │ │ ff │ frication frequency │ 39.06 Hz │ white noise frequency: 60 ─ 2344 Hz ("Sh") │ └───────────┴──────────────────────┴─────────────┴────────────────────────────────────────────────┘ See: http://web.inter.nl.net/hcc/davies/esp7cpt.htmltransitions and timing by mcstarPropTermialTract.zip
http://forums.parallax.com/showthread.php?89291-Singing-monk-squad/page4
http://forums.parallax.com/attachment.php?attachmentid=48624&d=1186636480
Propeller Speech Video
Propeller Speech Video Inside Scoop
Now you can hear the chip on a youtube video..
www.youtube.com/watch?v=LAAlE_G8_SI
Which was done by messing around with this...
http://forums.parallax.com/showthread.php?p=613308
Propeller Chip Speech Talk Guide
Other chips, systems, history
eSpeak
open source speech app to review for the english text to phonetic conversion:
http://espeak.sourceforge.net/
Free TTS another open source project
http://freetts.sourceforge.net/docs/index.php
SAM - Software Automated Mouth
http://forums.parallax.com/attachment.php?attachmentid=62887&d=1250209878
original documentation for the Atari version
http://www.retrobits.net/atari/sam.shtml
http://forums.parallax.com/showthread.php?115165-Text-To-Speech
downloaded SAM plus a C64 emulator and dissassembler
http://www.members.tripod.com/the-cbm-files/speak/
http://www.ccs64.com/
A good disk image is here
http://www.emuasylum.com/forums/showthread.php?t=31785
Devantech SP03 similar to EMIC modules based on the same WTS701 chip
http://www.robot-electronics.co.uk/htm/Sp03doc.shtml
http://forums.parallax.com/showthread.php?115165-Text-To-Speech
Votrax SC=01
http://en.wikipedia.org/wiki/Votrax
V8600A module from RC systems
http://www.rcsys.com/modules.htm
SpeakJet chip http://www.magnevation.com/
SoftVoice http://www.text2speech.com/
"Computalker" from 1978 Chip says: A year and a half ago, I found a site that documented a speech synthesizer product called "Computalker" from 1978, which was made by a small company in southern California. It goes into depth about what you have to do, once you have a synthesizer, to make speech sounds. Back then, that synthesizer was necessarily largely analog, but these days, digital silicon has enough horsepower to realize it all in software. Here is the site's url from the Netherlands:
http://web.inter.nl.net/hcc/davies/esp7cpt.html
Text-to-Speech SPO3
http://www.warburtech.com/modules/sp03.speech.synthesizer/
www.robot-electronics.co.uk/htm/Sp03doc.shtml
Color, Light Intensity, Ultrasonics
Simple Bee Analogy
Bees are rather complex insects, especially when trying to duplicate all their capabilities with a robot. For example, Bees can seek out color, smell, taste, vision, and touch vibrations. Combine that with path making, dancing, directional navigation, and special roles of reproduction, food generation, protectionism, hive creation, and randomizatiom, and the Bee is a rather complex organism.
http://ag.arizona.edu/pubs/insects/ahb/inf6.html
http://ag.arizona.edu/pubs/insects/ahb/lsn23.html
http://wiki.answers.com/Q/What_is_the_honey_bee%27s_senses
http://wiki.answers.com/Q/Do_honey_bees_have_any_sense_of_hearing
http://www.beeclass.com/dts/world_of_bees.htm
Honey bees have been found to distinguish between sweet, sour, bitter and salt, and thus have a sense of "taste." Honey bees use their antennae to gauge the width and depth of cells while constructing comb. They also communicate via touch during bee dances. Bees can see many colors but they do not see red. On the other end of the spectrum, we can't see ultraviolet and honey bees can.
The discussion is how much of a bee's work can we do with a Propeller Brain? Let's break this down into parts.
Color Sensor
Parallax offers a Color Sensor for $59.99 TCS3200-DB Color Sensor
detect and measure a nearly limitless range of visible colors
From Parallax: TCS3200 Color Sensor Daughterboard is a complete color detector, including a TAOS TCS3200 RGB sensor chip, white LEDs, collimator lens, and standoffs to set the optimum sensing distance. It plugs directly into the BASIC Stamp-2pe Motherboard or Propeller Backpack and will also interface to any other BASIC Stamp module or Propeller board using the optional DB-Expander SIP Converter (#28325). The TCS3200-DB can detect and measure a nearly limitless range of visible colors. Applications include test strip reading, sorting by color, ambient light sensing and calibration, and color matching, to name just a few. The TCS3200 has an array of photodetectors, each with either a red, green, or blue filter, or no filter (clear). The filters of each color are distributed evenly throughout the array to eliminate location bias among the colors. Internal to the device is an oscillator which produces a square-wave output whose frequency is proportional to the intensity of the chosen color. Read the documentation below and check out the Color Matching Demo for more detailed information.
ColorPal
Parallax offers the ColorPal for $19.99
miniature color and light sensor
From Parallax: The ColorPAL is a miniature color and light sensor which, through its RGB LED, doubles as a color generator. For sensing color, the ColorPAL uses its LED to illuminate a sample, one color component at a time, along with a broad-spectrum light-to-voltage converter to measure the light reflected back. The amount of light reflected from the sample under illumination from each red, green, and blue LED can be used to determine the sample’s color.The ColorPAL works with non-fluorescent reflective surfaces, preferably those in contact with its light shroud. For a full comparison of the ColorPAL to the TCS3200-DB Color Sensor, please refer to the chart in the ColorPAL documentation.
- Detects a full range of colors, and outputs data as RGB (Red/Green/Blue) components.
- Detects broad-spectrum ambient light with sensitivity down to 44µW/cm2 per lsb.
- Generates 24-bit color using onboard RGB LED.
- Plugs into servo headers (with optional cable) or wireless breadboards.
- Single-pin interface uses a simple serial protocol to define and initiate color detection and generation.
- Color detection and generation details handled by onboard microcontroller.
- Onboard EEPROM for saving custom color detection and generation programs.
- Autorun feature permits running a pre-designated EEPROM program with only a power supply.
- Power requirements: 5.0 VDC
- Communication: Serial 1-Wire (asynchronous serial, open drain)
- Dimensions: 1.72 x 0.90 x 0.65 in (44 x 23 x 17 mm)
- ColorPAL Documentation (.pdf)
- Color Matching Program and BASIC Stamp Sample Files (.zip)
- ColorPAL VGA Demo files [spin] (.zip)
- ColorPAL Sense [spin] (.zip)
Light to FrequencyFrom Parallax TSL230R Light to Frequency Converter $5.99
This device will measure light intensity and output a corresponding frequency.
The Texas Advanced Optical Systems (TAOS) TSL230R sensor precisely measures light using an array of photodiodes, with an output of digital square waves. The TSL230R has an input dynamic range of 160dB; that is, it can measure light over a range of 100,000,000-to-1. The TSL230R programmable light-to-frequency converter combines a configurable silicon photodiode and a current-to-frequency converter on single monolithic CMOS integrated circuits. The output can be either a pulse train or a square wave (50% duty cycle) with frequency directly proportional to light intensity. The sensitivity of the device is selectable and the output frequency can be scaled by one of four preset values. An output enable (OE) is provided that places the output in the high-impedance state for multiple-unit sharing of a microcontroller input line.
- High-resolution conversion of light intensity to frequency with no external components
- Programmable sensitivity and full-scale output frequency
- Communicates directly to a BASIC Stamp or SX microcontroller
- Absolute output frequency tolerance of +/- 20%
- Nonlinearity error (typically 0.2% at 100kHz)
- Stable over wide variety of temperatures
- Package: 8-pin DIP
- Power requirements: 2.7 to 5.5 VDC
- Communication: PWM
- Dimensions: 0.31 x 0.39 x 0.13 in (7.97 x 9.97 x 3.30 mm)
- Operating temp range: -13 to +158 °F (-25 to +70 °C)
- TSL230R v1.0 Documentation (.pdf)
- BASIC Stamp Code for TSL230R (.zip)
- N&V column "Look into the 'Eye from TI'" #21 (.pdf)
- N&V code "Look into the 'Eye from TI'" #21 (.zip)
- BASIC Stamp Experiments using the TSL230 by Mark Hughes (.pdf)
- Data Sheet (.pdf)
- Sensor Objects for Propeller Programmers
UltrasonicsPING))) Ultrasonic Sensor $29.99
Parallax's PING)))™ ultrasonic sensor provides a very low-cost and easy method of distance measurement. This sensor is perfect for any number of applications that require you to perform measurements between moving or stationary objects. Naturally, robotics applications are very popular but you'll also find this product to be useful in security systems or as an infrared replacement if so desired. You will definitely appreciate the activity status LED and the economic use of just one I/O pin. The Ping sensor measures distance using sonar; an ultrasonic (well above human hearing) pulse is transmitted from the unit and distance-to-target is determined by measuring the time required for the echo return. Output from the PING))) sensor is a variable-width pulse that corresponds to the distance to the target. Interfacing to the BASIC Stamp and Javelin Stamp microcontrollers is a snap: a single (shared) I/O pin is use to trigger the Ping sensor and "listen" for the echo return pulse. And the intelligent trigger hold-off allows the PING)))™ to work with the BS1! An onboard three-pin header allows the PING))) to be plugged into a solderless breadboard (on a Boe-Bot, for example), and to be connected to its host through a standard three-pin servo extension cable.
Click to Watch Video
Cyperbolic Reflector
From Gadget Gangster
Ping))) Cyperbolic Reflector
Improve the distance and
sensitivity of your acoustic
sensor
Image CAM, Object Detection, Infrared
CMUcam
CMUcam $139.99 From Parallax: Track images with the Boe-Bot® Robot CMUcam! The Boe-Bot CMUcam ships with printed documentation, CD-ROM with demo programs, and mounting directions. The Boe-Bot CMUcam (#30051) is designed specifically for the Parallax Boe-Bot Robot; allowing the Boe-Bot to find and track colors. Download the complete manual and video at the bottom of the page for more detailed information.
- Track user defined color blobs at 17 frames per second, find the centroid of the blob
- Gather mean color and variance data Arbitrary image windowing
- 80x143 resolution
- Automatically detect a color and drive a servo to track an object
- Slave parallel image processing mode off a single camera bus - advance function
- Adjust the camera's image properties - advanced function.
- Ability to control 1 servo or have 1 digital I/O pin - advanced function
- Power requirements: 4.75 to 5.25 VDC
- Communication: Synchronous Serial at 9600 baud
- Dimensions: approx. 2.93 x 4.53 x 2.1in (74.4 x 115 x 53 mm)
- Operating temp range: -32 to +158 °F (-0 to +70 °C)
- Boe-Bot CMUcam Manual (.pdf)
- Boe-Bot CMUcam Image Chip Info (.pdf)
- Boe-Bot CMUcam Source Code Demo (.zip)
- CMUcam Video (.wmv)
- CMUcam ver. A archive files (.zip)
The Boe-Bot CMUcam includes a printed user manual, cd-rom with sample code, and a pre-installed custom mounting bracket with two screws. There are other CMUcam kits available which may have different parts, features, and documentation that aren't designed to work specifically with the Boe-Bot robot. The Boe-Bot CMUcam uses the same PCB as the general purpose package (described below) but does not include the parts that convert the serial port to RS232C levels compatible with a PC serial port. It also doesn't include the voltage regulator and jumper headers since they aren't required when using the BASIC Stamp microcontroller. This version can be modified for use with a PC by adding the parts that were left off the board, although the Parallax warranty is voided if you modify the board. While you cannot directly view a picture from the camera on your PC with the Boe-Bot CMUcam setup, a demo program is included that allows you to display the tracking data packets from the CMUcam on the PC debug screen. In some ways this is better than viewing a raw camera picture because you are seeing the data your robot will be using to "see" its world.A general purpose CMUcam PC evaluation package doesn't include the mounting brackets for the Boe-Bot robot. If you wanted to use this package with the Boe-Bot robot you would need to build a mounting bracket and remove the Max232 chip. Then you would have to add wires from the TTL level serial port to the Boe-Bot robot's BASIC Stamp module. You would also need to add wires to connect the CMUcam to the Boe-Bot robot's battery pack. One potential problem with this is that you can damage the CMUcam or BASIC Stamp module when using the TTL level serial port connection if the power to both is not turned on and off at the same time. The Boe-Bot robot version of the CMUcam can be modified to be the same as the non Boe-Bot robot version of the CMUcam then it will work with the CMU Java program (but voids Parallax warranty).
In order to use the Java PC program the CMUcam needs to operate at 115,200 baud. The Boe-Bot robot version of the CMUcam is strapped to operate at 9600 baud only. You also would need to translate the TTL level serial port to standard RS232C levels for connection to a PC serial port.
Photoresistor
Phototransistor
From Parallax:
Phototransistor
Infrared
From Parallax
IR Transmitter Assembly Kit
Human Detection
PIR Human Detector
PIR Sensor $9.99
The PIR (Passive Infra-Red) Sensor is a pyroelectric device that detects motion by measuring changes in
the infrared (heat) levels emitted by surrounding objects. This motion can be detected by checking for a
sudden change in the surrounding IR patterns. When motion is detected the PIR sensor outputs a high
signal on its output pin. This logic signal can be read by a microcontroller or used to drive a transistor to
switch a higher current load. The PIR Sensor detects motion up to 20 feet away by using a Fresnel lens and infrared-sensitive element to detect changing patterns of passive infrared emitted by objects in its vicinity. Inexpensive and easy to use, it's ideal for alarm systems, motion-activated lighting, and holiday props. The PIR Sensor is compatible with all Parallax microcontrollers. BASIC Stamp and SX/B code is available under Downloads below, and Spin code is posted to the Propeller Object Exchange.
- Detection range up to 20 feet away
- Single bit output
- Jumper selects single or continuous trigger output mode
- 3-pin SIP header ready for breadboard or through-hole projects
- Small size makes it easy to conceal
- Compatible with BASIC Stamp, Propeller and many other micrcontrollers
- Alarm Systems
- Holiday animated Props
- Motion-activated lighting
- Power requirements: 3.3 to 5 VDC
- Communication: single bit high/low output
- Dimensions: 1.27 x 0.96 x 1.0 in (32.2 x 24.3 x 25.4 mm)
- Operating temp range: +32 to +121 °F (0 to +50 °C)
- PIR Sensor Documentation v1.4 (.pdf)
- Sample Source Code for BS1, BS2, SX/B (.zip)
- Scary Terry's PIR Sensor Report (Off Site)
- Sensor Objects for Propeller Programmers
Parallax Perspective:Click to Watch Video
The brain regulates the body which is nerved with massive numbers of sensors, including an autonomic system which functions in the background without our knowledge. The brain is not fully understood. Though it has a finite number of neurons (estimates vary or perhaps brains vary), it's capacity to engage those neurons (in memory for example) far exceeds their numbers, i.e. they have some unknown way of combining and becoming more capable.
The life expectancy you speak of is usually not a limitation of the brain. It is often another part of the body that fails first. Geneticists now believe it will be possible to extend the human life by 200 years in the future with gene technology.
We are still at the beginning of understanding the brain. In the future, it may be possible to non-invasive engage the brain to tap into its knowledge-base for some preservation, even transferal. A lot is riding on the creation and expectations of Artificial Intelligence.
Today, NMR and other neural sensors can interpret brain functions in a fundamental way. Researchers have found a way to create images from our thoughts. Game programmers can use the neural energy of the brain to move virtual objects on a screen.
The human brain is mystery and we simply don't know why it has such great capacity in so many ways.
Neural Map & Interactive Brain Basics
Neural Map
This is a neural map made with Nuclear Magnetic Resonance imaging.
http://braininfo.rprc.washington.edu/TemplateNeuroMaps.aspx?page=http://neuromaps.braininfo.org:8180/overlay-showit.jsp?id=197020
Brain Basics
Brain Basics is an interactive map of the Brain.
http://www.brainline.org/multimedia/interactive_brain/the_human_brain.html?gclid=COHzrP_jjqcCFQPgbgodvjj4cg
Introduction to the Human Brain
http://www.newscientist.com/article/dn9969-instant-expert-the-human-brain.html
The complexity of the connectivity between these cells is mind-boggling. Each neuron can make contact with thousands or even tens of thousands of others, via tiny structures called synapses. Our brains form a million new connections for every second of our lives. The pattern and strength of the connections is constantly changing and no two brains are alike. It is in these changing connections that memories are stored, habits learned and personalities shaped, by reinforcing certain patterns of brain activity, and losing others.
Wins Jeopardy over humans
Breaking News!
http://www.usatoday.com/tech/news/2011-02-17-watson17_ST_N.htm?csp=34news
Watson won decisively after three days against Ken Jennings, left, and Brad Rutter on Jeopardy!
Watson, the IBM computer created to be a champ-challenging contestant on Jeopardy!, chewed up and spat out humanity's finest knights of trivia Wednesday night in a $77,147 drubbing of past record winners Ken Jennings ($24,000 total) and Brad Rutter ($21,600).
Fatal Day of Reckoning
So has the fatal day of reckoning arrived, foretold by Frankenstein, 2001: A Space Odyssey and, of course, The Terminator series of man-vs.-machine movies? Even trivia, one of humanity's favorite pursuits, has yielded to the mighty computer.
The Machine
Watson is a Linux system powered by 10 racks of IBM Power 750 servers with 2,880 processor cores. It is capable of operating at 80 teraflops, or 80 trillion floating point operations per second.
The Man
The computing specs of the human brain involve some guesswork, but many estimates, based on the estimated number of neurons and synapses in the brain, put the processing power at about 100 million MIPS, or 100 million million instructions per second. In floating-point terms, estimates have made it 100 petaflops (100 quadrillion flops). Of course, since the brain also is occupied with running the functions of the human body, how many of those flops are focused on the question at hand at any given time is a mystery.
http://gcn.com/articles/2011/02/10/watson-vs-human-brain-tale-of-the-tape.aspx
Implications
http://www.poughkeepsiejournal.com/article/20110217/BUSINESS01/102170338/Watson-tops-human--Jeopardy---champs--but-IBM-is-real-winner
"The implications of this technology in the coming years are going to be phenomenal," said Ross Mauri, IBM vice president for enterprise process transformation and a Marist grad.
"We have people lining up to partner with IBM, work with us and find new applications," said Casimer DeCusatis, an IBM distinguished engineer in the Systems and Technology Group.
The Technology
Watson technology is designed to answer questions from an internal database that occupies 15 terabytes of memory, or 15 trillion bytes, a byte being the basic unit of memory. IBM figures the Watson technology will find real-world uses besides keeping TV host Alex Trebek company.
Applications
There's health care, helping doctors gather data they need to diagnose and treat disease . There's government service, where Watson could help provide people with information from agencies. In travel, Watson could help tourists with specific information about places they are visiting. And in customer service, Watson could improve online self-service help desks, IBM's material says.
I'll take "Computer Overlords" for $500
Watson, an IBM supercomputer, overwhelmed its human challengers in a three-day "Jeopardy" tournament, finishing with a final total of $77,147.
http://heraldnet.com/article/20110217/BLOG08/702179945/-1/NEWS01
Making Machine Money
Watson may be smart, but it misplayed things by hitting "Jeopardy" first. It could have made a lot more money by starting small and working its way up, beginning with "Wheel of Fortune," then "The Price is Right" and "Deal or No Deal," then "Are You Smarter Than a Fifth-Grader."
Organizing Brain modules
The Brain design is now a top down approach.
This indicates, in the vertical orientation, a top
board with various responsibilities. Some of these
elements are activated on the fly while others will be
incorporated full time.
The following initial setup is reviewed:
- mouse
- keyboard
- TV
- testing
- speech recognition
- speech synthesis
At a later date, the developed moduleswill be transferred to other boards for more
even distribution of duties. Duties are also
transferred when the chip runs out of resources.
Protection for wiring
The Brain has an EXOskeleton skin
of composite material consisting of
both inner and outer shrouds.
The Brain already has skin which was recently
transferred to protect and hide the TV when not in use
or required. This skin is black but does not protect
the wiring. Additionally the boards have LEDs and it's
a good idea not to block the visual cues from these
data and programming indicators. Therefore, a new
translucent skin is introduced. This is an outer skin
layer of material that serves these purposes.
- protects wring
- provides LED visual cues
- is almost weightless
All skinning material is from recycled containmentsfound in China. This is just a fitting. In the final skin,
the unit will extend from top to bottom in sections.
Covers TV
The Inner Brain Skin is the
access cover to the Brain Stomach
The first of two skin types is known as the Inner Skin
and it's a removable section for the TV. This skin
is the "access cover" to the Brain Stomach where
peripheral guts may be hosted or permanently attached.
The Brain Inner Skin snaps into place. No screws,
bolts, nuts or hardware needed. This enables rapid
TV deployment for viewing dreams and data. The black
skin is opaque and made from recycled containments
found in China.
Simple methods to install tv
A Parallax Brain TV is made by installing the
TV into the guts of the Brain
The Inner Shoud is removed showing the
location of TV inside the Brain Stomach
Brain TV is important. Its primary functions are:
- show thinking
- illustrate unfolding dreams
- access portal to programming language
- brain parametric display
- updating stats
- a vision eye portal
- other sensor view dash
The Brain TV is wedged in between two Protosand additionally held in place at the base with
a small amount of hot melt glue applied to the
obverse Proto. This allows the TV to continue
with the pivot function for viewing adjustment.
Unveiling the Brain's 1st functions on TV
In astronomy, new built telescopes celebrate their unveiling by
"First Light," when the instrument has the light of a distant
celestial object, like a star or galaxy, first impinge on its newly
formed optics.
In a similar "light," the Brain was unveiled in "First Light," last
night when the TV display was lit with the first thinking program.
Although simplistic in nature, as first programs may be, it
represents a somewhat historic occasion if you're part of the
Open Source Brain Initiative.
Brain's 1st Light - the first program output to
TV demonstrating the speed at which data can
display. (shown in Vertice Mode)
Keyboard, TV and the green light - all is a "go"
with the Brain! Brain TV is designed as output
for experimenting with this example of
EmbeddedBasic, a language for the Propeller
created by Bean.
Another favorite Propeller language is
FemtoBASIC developed by Mike Green.
Although there are almost 170 programming
languages available for the Propeller, it is
undecided at this time which ones or how
many will be adapted to run on the Brain.
Online Brain Search Index Page16 Post 304
http://forums.parallax.com/showthread.php?124495-Fill-the-Big-Brain&p=978403#post304
Report on the current Brain Project
This is the current view of the Brain project which has
received First Light on Saturday February 18th, 2011.
I am Brain...
The current status of the Brain is
reviewed in this post. Note removal
of the inner skin, outer skin, cryo, and
bus bundle distro so that the inner
portion of the brain is more readily
seen.
The first post in this thread, "Fill the Brain," appeared
August 5th, 2010. It is now one half year later and work
on the Brain has continued throughout the 6-month
duration.
At this time, the Brain has run four languages.
The photo shows the current appearance of the Brain.
While boards are up and running, there is still wiring
that need to be added and completed.
Capabilities continue to increase. In the current state,
the Brain has
Constituent Brain Components
- 22 boards
- TV
- VGA
- Audio In
- Audio Out
- Keyboard
- Mouse
- EEPROM x 22
- Data LEDs
- 22 Solderless Breadboards
- Summit
- Brain Stem
- Brain Spans
- Brain Base
- Brain Stomach
- Spacer System
- Card Cage
- Vertices
- EXOskeleton
- Exterior Skin
- Interior Skin
- Cryogenics Test
- Flip Mounting
- Schematic Drawings
- PPPB Modifications
- Small LCD
- Large LCD
SoftwareCapabilities being Integrated
(Partial List)
- Electronic Voice
- Electrical Lips
- Electronic Speech Recognition
- Singing
- Electronic Tongue (Sweet, Sour, Salt, Bitter)
- Nose
- Ear
- Inner Ear Balance
- Motion Control (Fwd, Back, Rotation)
- Motion Conrol GUI
- Vision Array (Human Detect, Ultrasonics, Infrared, Light Level, ...)
- Cryogenics
- Bundle Distro
- Battery Pack
- Control Panel
- More Communications
- Machine Intelligence
- Dreaming
- Sensors
- Enhanced Operating System
Ability List AnticipatedSpeak, listen, move, smell, taste, sing, sound, play chess, dream,
think, see, ...
Sources for Prop Chess
This is a single Propeller chip Chess game that can
become the basis of a multi-prop Chess program for
the Brain.
Prop Chess [Human VS Propeller] - VGA by Rayman
Chess6_XGA - Archive [Date 2009.06.20 Time 11.04].zip
http://forums.parallax.com/showthread.php?p=817111
http://forums.parallax.com/showthread.php?113827-Prop-Chess-%28for-VGA%29-Human-Vs.-Propeller
http://www.rayslogic.com/propeller/propeller.htm
Can you beat your Prop at Chess? This is by no means complete. I think it knows all the rules and plays fairly. Also demonstrates a mouse.
Video Chess Tests by Rayman
http://forums.parallax.com/showthread.php?104287-Chess-TV-%28test%29
Human VS Human by Rayman
http://forums.parallaxinc.com/forums/default.aspx?f=25&m=289824
Chess4_MoveTest.zip
Here's a working chess program for 2-players. It knows all the rules and can detect Check, Checkmate, Stalemate. It knows about Castling and En Passant.
Robotic Propeller ChessBot by Norris56
http://forums.parallax.com/showthread.php?114987-ChessBot-A-Chess-Playing-Robot
Chess GUI by Rayman
http://forums.parallax.com/showthread.php?105243-Chess-GUI
Enlarging the image of a Parallax 3.5-inch TV
I'm experimenting with a DIY flat light weight plastic molded 10.5 inch diameter Fresnel lens in front of the 3.5-inch Parallax monitor. It's interesting as tests show it nearly doubles the apparent screen size but at the cost of introducing reflections and some optical aberrations. I plan to do further tests with it. It may be useful with a good mount and a little helpful only if the screen fonts are already legible and tac sharp.
What is a Fresnel Lens?
http://science.howstuffworks.com/question244.htm
The thin piece of plastic used here is called a Fresnel lens. It is flat on one side and ridged on the other. Fresnel lenses we first used in the 1800s as the lens that focuses the beam in lighthouse lamps. Plastic Fresnel lenses are used as magnifiers when a thin, light lens is needed. The quality of the image is not nearly as good as that from a continuous glass lens, but in lots of applications (like your RV), perfect image quality is not necessary. The basic idea behind a Fresnel lens is simple. Imagine taking a plastic magnifying glass lens and slicing it into a hundred concentric rings (like the rings of a tree). Each ring is slightly thinner than the next and focuses the light toward the center. Now take each ring, modify it so that it's flat on one side, and make it the same thickness as the others. To retain the rings' ability to focus the light toward the center, the angle of each ring's angled face will be different. Now if you stack all the rings back together, you have a Fresnel lens. You can make the lens extremely large if you like. Large Fresnel lenses are often used as *solar concentrators
Brief History of Fresnel Lenses
http://en.wikipedia.org/wiki/Fresnel_lens
A Fresnel lens (pronounced /freɪˈnɛl/ fray-NELL) is a type of lens originally developed by French physicist Augustin-Jean Fresnel for lighthouses. The design allows the construction of lenses of large aperture and short focal length without the mass and volume of material that would be required by a lens of conventional design. Compared to conventional bulky lenses, the Fresnel lens is much thinner, larger, and flatter, and captures more oblique light from a light source, thus allowing lighthouses to be visible over much greater distances.
This before photo shows the Brain with a 3.5-inch TV, too small
to read from a distance
Suddenly the TV Display appears about 75% of the size of a
compared adjacent PC monitor (13.9-inch). The after photo
shows enlargement along with a 20% image degradation and
added reflections
Is the TV screen improved? You can be the judge. Admittedly, the screen can be improved
from this image by moving the lens closer to the TV and decreasing the viewing position.
A shade or darkened room can minimize reflections. Fresnel lenses are not optical coated.
These tests made are with a large Fresnel Lens, size 8 inches by 10.5 inches. Office Fresnel lenses are sold at Office Max for the purpose of magnifying pages from a book. Typical price is about $14.95.
The purpose here is to increase the apparent size of the Brain's tiny display. The TV has a mere 320 x 240 pixels and most 32-character text lines, especially those with half height characters, nearly impossible to work with.
Use of the Fresnel lens does indeed magnify the image. In fact, at a distant viewing angle, the screen can nearly (apparently) double in size. But, does this improve visual quality?
It was found that the lens cannot improve a tiny font that is not tac sharp and and very clear. It can somewhat improve larger fonts that can be read ok without the lens.
The lens is not optical quality. The plastic introduces optical aberrations and reflections. It degrades an image subjectively by approximately 10 or 20%.
In the before and after tests, the enlargement is dramatic. But is the text improved? Look at the photos and you can judge.
Experiments will continue and some ideas for improvements will be implemented. Some improvements are suggested:
Adding Extended Color BASIC 1.0
Color BASIC is booted and running on the Brain
The latest programming language added to the Brain is Extended Color BASIC 1.0 by Tandy. This is fb TandyBasic in Spin by Tomas Rokicki. (see photos)
http://forums.parallax.com/showthread.php?113091-ULTIMATE-List-of-Propeller-Languages&p=809630
http://forums.parallax.com/showthread.php?85679-fb-my-first-program-for-the-propeller
Downloads: fb.zip
Tandy Extended Color BASIC has a retro GreenScreen
This brings the total number of languages on the Brain to five. Official install posts will follow respective languages.
- PASM
- Spin
- FemtoBASIC
- EmbeddedBASIC
- Extended Color BASIC 1.0
To get Extended Color Basic running, I had to modify a statement in the keyboard driver by simply remming out the statement. The statement is identified by the error. The language is running on a Parallax Demo Board located at the Brain Summit. Keep in mind there are 168 possible languages for the Brain. Just how many of these will be installed remains to be seen. Apparently we're looking for BASIC languages that can reside in eeprom and automatically start up at power on.Here's a quick whip program in Color BASIC to display incrementing screen numbers
Data output to screen using
the above program
There's not much information about this version of Color BASIC so I had a look at the Spin code and came up with a small amount of information for a mini-manual.
fb Mini-Manual
"it's a fairly functional Tandy Color Computer from 1980!" Chip Gracey
Commands
IF
THEN
INPUT
PRINT
GOTO
GOSUB
RETURN
REM
NEW
LIST
RUN
RND
Boolean Expressions
a < b
a > b
a <> b
a == b
a => b
a =< b
Math functions included
a + b
a - b
b * b
b / b
(others not checked)
Error Reporting
"SYNTAX ERROR", 0
"INVALID LINE NUMBER", 0o
Color Screen Commands
Default Green Screen
Command Line
Yes
Cursor
Yes
Keyboard
Yes
TV
Yes
Graphics
Yes, Graphics Driver v1.0 by Parallax
Points, lines, arcs, sprites, text, and polygons are rasterized into
a specified stretch of memory which serves as a generic bitmap buffer.
The bitmap can be displayed by the TV.SRC or VGA.SRC driver.
See GRAPHICS_DEMO.SRC for usage example.
Chip Gracey Comments
Rokicki, Wow! I wouldn't have believed it if I hadn't run it! For those of you who haven't tried this, it's a fairly functional Tandy Color Computer from 1980! It comes up with a prompt and you can type in programs via keyboard and run them (using the Demo Board). It uses line numbers. I typed in this, and it ran:
10 print "x";
20 goto 10
run
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
I never expected to see something like this, especially so early. Rokicki, I think you must have done this enough times on enough systems that you could do it in your sleep now. I can't think of any other explanation for how you would know WHAT to do so quickly to make a Tandy CC like this. Please note the new efficient VGA character display I posted last night. It will free up almost half the RAM your tv_terminal is using now, plus it's WAY faster. With more memory, you could do way more. I can't believe you even packed in an interpreter!
Of all TV text text drivers tested on the 3.5-inch TV, the best in terms
of readability, sharpness, and clarity is the TV Text Demo v1.0 by
Chip Gracey. This test uses the internal ROM font.
The Brain is running the Propeller TV Text Test by Chip Gracey
The driver uses these Propeller fonts for greatest clarity
and visibility, even on the tiny 3.5-inch Parallax TV.
The driver and the demo is in the OBEX Object Exchange.
http://obex.parallax.com/objects/67/
This is a derivative of TV Terminal but uses the Propeller’s internal font
and uses much less memory. OBJ and VAR require only 2.8KB.
TV_Text_Demo.spin
TV_Text.spin
TV.spin
Connecting peripheral robots via wireless interface
One Brain experiment can involve the connection of n-number of Penguin
robots for group swarming, group dancing, and group construction.
Group Construction is when the Brain commands a larger number of
robots to accomplish specific tasks, all working in unison, to assemble
various construction object projects.
Data and commands to and from the Brain are better accomplished with
a wireless interface when remote locations are involved. The Brain will
communicate with peripheral devices. For example, the Brain mouth
and tongue can be located externally and link to the primary Brain functions.
The wireless communication system will use serial programs that can
send and receive data and commands. The idea uses a Parallax #27980
and #27981, transmitter and receiver, to send and receive from the host robots.
433 mHz Parallax RF Receiver Manual (.pdf)
433 mHz Parallax RF Transmitter Manual (.pdf)
433RadioCRCV1.0 (.zip)
The Parallax RF modules provide a very easy and low-cost method of sending data between microcontrollers or to a PC from 500 ft+ line-of-sight (depending on conditions). The receiver unit has a power down feature and a RSSI signal for strength indication. The transmitter unit has a power down feature.
- High-speed data transfer rates (1200 ~ 19.2k Baud depending on controller used)
- SIP header allows for ease of use with breadboards
- Compatible with all BASIC Stamp® modules (including BS1 and Javelin Stamp) and SX chips
- As easy to use as simple SEROUT/SERIN PBASIC instructions
- Power-down mode for conservative enter usage (longer battery life)
- Line-of-sight range of 500 feet (or greater depending on conditions)
- Remote Controlled Boe-Bot® robot
- Wireless data acquisition
- Remote sensors and triggers
- Power requirements: 5V +/-10%
- Current: ~10 mA normal operation & ~3mA during power down
- Date Rate: 12,000 - 19.2 K baud (controller dependent)
- Transmission: 500 ft+, based on environment conditions
- Dimensions (with antenna): 0.9 x 3.6 in (22.9 x 91.4 mm)
- Operating Temperature: -40 to +158 °F (-40 to +70 °C)
Parallax pageshttp://www.parallax.com/Store/Accessories/Communication/tabid/161/CategoryID/36/List/0/Level/a/ProductID/113/Default.aspx?SortField=ProductName%2cProductName
http://www.parallax.com/StoreSearchResults/tabid/768/txtSearch/DISCONTINUED/List/0/SortField/4/ProductID/112/Default.aspx
Parallax board serves wireless transmit/receive
Board 23 is a BASIC Stamp Home-
work Board, now added to the
Brain- a green board visible at top
left. This board's function will likely
serve up wireless serial transmissions
and reception to control robots,
peripherals and more remote Brain
components and modules. (seen
here without the transmitter or
receiver)
Today the Brain received a new add-on board mounted near the Summit.
The board has one BS2 processor which is compatible with the Parallax
Transmitter and Receiver.
The Summit location raises the 433mHz antennae to the highest position
in the vertical flip mode for greatest range and least interference. This adds
the real estate of another breadboard for holding the transmitter and
receiver.
Another added aspect of this mounting is the antennae do not need removal in either of the flip positions horizontally and vertically.
The total number of boards is now twenty-three with a varying number of
processors, both in quantity and type.
The board is mounted with two sets of two angle iron connected together
and bolted to the green board.
Travel through the Brain's Inner space and
document the journey with your Google Camera!
Take a fantastic journey through the inner space of the Brain, exploring three dimensional aspects of thousands of Brain components, defined by Master Google Sketch-Up Artist NikosG.
___________________________________________________________________________________________________________________________________________________
What hidden treasures lurk inside the Brain, deep down in the stomach, or along the inner cavity walls where no has visited from the inside out? For the first time, using computerized CAD, we can take a most fascinating inner Brain journey! Like a Star Wars three dimensional journey, this actual fly-by takes you inside the brain as you whiz by sides of Parallax Propeller boards in this highly detailed view showing thousands of components! The view faces the Brain Summit which is the exit point at the top of the Brain in the vertical Flip Mode. Fly through the Brain and exit out of the Summit, then turn around to skim across the detailed EXOskeleton.
Based on highly accurate three dimensional models provided by master sketcher NikosG of Greece, who first sketched a single Parallax Propeller Proto Board (detailing every hole and socket with added solderless breadboards) and then cloned it twenty one times, this trip takes you where no one has gone before. Twist and turn as you navigate the unseen uncharted interior stomach of the Brain, and zoom along from the inside out!
Index page 16 post 304
Apps developed with free open source 3D package
Brain 3D Image by SketchUp artist NikosG
This view shows the open side of the Brain
which has three boards and mounts two
LCD displays. Not shown is the added TV,
Propeller Demo Board at the top, and a
recently added board also at the top
(a BS2 Homework Board to help dedicate
telecommunications).
Google Sketchup is the 3D choice for illustrating the Brain.
There are numerous aspects to using a 3D model.
- develop exterior flybys
- make movies and step-stills
- view all data in xray views
- create various flip brain views at any angle
- develop interior views and views of hidden spaces
- makes add ons more easy
- allows testing before add on
- ideal for Brain manual illustrations
- wireframe and extra modes
- numerous extras
The Google 3D Modeling page is herehttp://sketchup.google.com/
Download for Windows and Mac OS is here
http://sketchup.google.com/download/gsu.html
Learn about SketchUp
View gallery
Brain Index page 16 post 304
Focus on Taste
We have opened up an exploratory thread here
Taste Sensor for the Propeller Chip
regarding a Brain Electric Tongue.
The idea is to create an Electric Tongue which can detect the four basic taste groups, salt, sweet, sour, bitter. Some ideas considered:
- spectrometer- reflected light is analyzed and chemical composition it determined
- artificial saliva helps detection of the sample
- a chemical litmus color paper analysis with color detection sensors
Research is ongoing and suggested are being accepted at the thread.The surface of the human tongue is covered with over
9,000 chemical detectors.
Brain Index page 16 post 304
Adding languages to the Brain
This brain test uses EmbeddedBasic, a language
by Bean with some assistance from Mike Green.
In Horizontal Flip mode, the Brain operates as
a console with TV output from EmbeddedBasic.
We are installing various languages into the Brain,
primarily languages that can output to the TV, and
have a keyboard driver. Booting from the eeprom
without intervention is also a feature that's given
priority.
__$WMc%__ writes: I've used EmbeddedBasic on my Propeller Professional Development prototyping board with the key board and a TV driver. Its just like an old TRS-80 but a lot faster. I'm waiting on an SD card reader to continue with this project. I'm using EmbeddedBasic on the Spinneret using Telnet. (see the Spinneret forums for EmbeddedBasic on the Spinneret by Bean)
This is like a remote PC terminal over the INTERNET. EmbeddedBasic (written by Bean and some assistance from Mike Green) is very much like FemtoBasic but it's compiled in PropBasic - PASM instead of Spin, so its much faster than FemtoBasic. Thought this might help your "Brain" project.
Brain Index page 16 post 304
Audio amp supplements headphones
It's not loud enough to yell at the neighbors but good enough to give a
beautiful singing performance in a small room made into a concert hall.
The Brain now has a small stereo audio amplifier set in place for voice
speech and singing. Mounting considerations will become a future
project.
A small Chinese Sansui amplifier now replaces headphones in the
Brain so speech and singing is now normally heard across the room
and within group environments, for giving speeches, lecturing, addressing
more than one person and singing performances.
The Sansui amp is used in several ways.
- USB powered
- Powered by internal rechargeable batteries
- Recharged by AC adaper
- 5Vdc input jack
The unit handles stereo sound input and output with two speakersapproximately 1.75-inch diameter each and two removable plug
cords. The audio and USB cords are each just over 2-feet long. The
model S90 amp has a power switch, bright blue LED power indicator,
power on/off slide switch, and a volume control.
The input cord has a plug compatible with the Parallax Demo Board's
input sound jack and the cord is long enough to reach when the Brain
is in the Vertical Flip Mode.
Currently the Brain Amp, which is 2-inches wide x 6 5/8" long x
1 3/16" deep, is set external to the Brain during use. However, in
another post, details will be given for mounting internally or externally
on the Brain.
Brain Index page 16 post 304
Faster sub index gets pasted into the master index
Previous Page 16
301 Propeller Brain Self Education Tutorials for Propeller Programming
302 Brain Searchable Photo Index Nearing completion
303 Brain Speech Recognition Talk to the Brain in your own language
304 New Fast Online Brain Search Index Faster searching without the PDF File
305 Creating Brain Speech - Parallax Propeller Takes the Lead as Speech Synthesizer Chip
306 Brain Senses - Focus on Vision Part 1 Color, Light Intensity, Ultrasonics (6 photos 1 vid)
307 Brain Senses - Focus on Vision Part 2 Image CAM, Object Detection, Infrared (5 photos)
308 Brain Senses - Focus on Vision Part 3 Human Detection (1 photo 1 vid)
309 Brain Capacity Question
310 Brain Capacity Reply
311 NMR Brain Map Neural Map & Interactive Brain Basics
312 Watson - Artificial Intelligence Brain Wins Jeopardy over humans (1 photo)
313 Brain Top Down Organization Organizing Brain modules
314 Brain Outer Skin Protection for wiring (1 photo)
315 Brain Inner Skin Covers TV (1 photo)
316 Installing Brain TV Simple methods to install tv (2 photos)
317 Celebrating The Brain's First Light Unveiling the Brain's 1st functions on TV (2 photos)
318 Brain Project Status Report on the current Brain Project (1 photo)
319 Play Chess Against the Brain Sources for Prop Chess (2 photos)
320 Brain Fresnel Tests Enlarging the image of a Parallax 3.5-inch TV (3 photos)
Current Page 17
321 Brain Color BASIC Programming Language - Adding Extended Color BASIC 1.0
322 Brain Text Test Demo
323 Brain Wireless Communications System - Connecting peripheral robots via wireless interface
324 Brain Receives Board 23 - Parallax board serves wireless transmit/receive
325 Spectacular Giant Brain Fly-Through! - Travel through the Brain's Inner space..
326 Brain Project Selects Google 3D SketchUp - Apps developed with free open source 3D package
327 Brain Senses - the Electric Tongue - Focus on Taste
328 Brain On EmbeddedBASIC - Adding languages to the Brain
329 Brain Voice Amplifier - Audio amp supplements headphones
330 Brain Sub-Index - Page 17 - Faster sub index gets pasted into the master index
331 Singing Brain - Brain singing on video with audio track
Brain singing on video with audio track
The Brain is now singing, as heard in this video's audio
track. What new functions will the Brain learn next? Who
knows?! One one thing is certain, we are the teachers and
the Brain is the student. Nothing to worry about at this
time, unless... the table is turned!
Movie demonstrates a singing brain
It's the smallest resolution video, and sideways, with the sole
purpose of audio to example the singing brain. It uses parts from
the demonstration programs found on the Propeller Parallax
Forum. Note: this is all accomplished with Propeller chips.
Note the fine machine accent and the purity of the tonality
and rhythm. The Spin code has control over the singing
parameters.
Eventually this will be supplemented with new singing
(need Bicycle Built for Two) but for now the goal it to get
everything working..