I think that NuPIC is a perfect solution for CW interpretation. It would require some front-end work to be done. I’m the one who chatted the questions in to Office Hours about audio coding last week, and I’m looking to start coding some audio front-end stuff, building on the code that already exists for that. I was looking more at audio music and spoken language decoding, but CW could be a good intermediate step. I need to learn more about the types and scope of variation in the code transmissions.
NuPIC is the brains that recognizes patterns, we just need to figure out the right sensory arrangement to see the most useful patterns. rich On Aug 20, 2014, at 11:21, Matthew Taylor <[email protected]> wrote: > Chris, > > Please keep in mind that this is very early stage technology. We are > working on the foundations of HTM with NuPIC, and we open-sourced the > codebase to get community involvement as soon as it was feasible. > True, NuPIC is not a turnkey solution for any problem at this point, > but our goals are to share this tech with anyone who wants to work on > it, and encourage motivated developers to craft solutions to > interesting problems. > > In the future, I imagine a library of community-provide encoders that > can be easily plugged into NuPIC. (For other musings about the future > of NuPIC, see [1].) But in the meantime, we have a lot of work to get > done. If you want to be a part of it, you could join our sprint > planning meetings [2] and open office hours [3]. > > [1] https://www.youtube.com/watch?v=QPkA6nJifOw > [2] > https://www.youtube.com/watch?v=oB71cqyRi9s&list=PL3yXMgtrZmDrtAuw9jJCNbaJmW3nSD3hC > [3] > https://www.youtube.com/watch?v=MWBFw4WoZxA&list=PL3yXMgtrZmDqsqo6hytKjhrkfFNEYDqfn > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Wed, Aug 20, 2014 at 7:59 AM, Chris Albertson > <[email protected]> wrote: >> I posted this same exact question here some weeks ago. I've not >> read your links yet but I will. >> >> My conclusion about NuPic is about the same as your #1, #2 and #3. >> That is you need a large "do it yourself" solution on top of NuPic, >> so I wonder what's gained, If you need to write you own encoder, >> layering and feedback and then extract the results (inverse encoder?) >> what is gained by using NuPic over some other NN library? Those >> "higher order sequences" would be handled in NuPIc by a hierarchy of >> CLAs that you would have to implement. >> >> I'm thinking now that recognizing CW is a lot like speech recognition. >> But the up front encoding needs to be some kind of phase locked >> loop on the "dit period" >> >> I also thought NuPIc would be great for this, just pass in the audio >> stream.... But I don't think it's up to the job. >> >> On Tue, Aug 19, 2014 at 9:39 PM, Mauri Niininen >> <[email protected]> wrote: >>> I am looking for some expert advice from NuPIC gurus here. >>> >>> I have been working on the problem of decoding Morse code from noisy, real >>> life signals as received using HF radios. I have implemented several types >>> of signal processing and machine learning algorithms trying to improve >>> accuracy and reduce decoding character error rate (CER) caused by various >>> reasons, such as >>> - poor signal-to-noise ratio >>> - signal fading due to RF propagation >>> - poor rhythm & timing of hand keyed CW >>> - rapid speed changes >>> - signal interference from adjacent frequencies >>> >>> If you are interested in this subject there is more detailed descriptions on >>> problems and solutions I have tested so far in here: >>> http://ag1le.blogspot.com/2013/09/new-morse-decoder-part-1.html >>> http://ag1le.blogspot.com/2014/06/new-morse-decoder-part-4.html >>> http://ag1le.blogspot.com/2014/07/new-morse-decoder-part-6.html >>> http://ag1le.blogspot.com/2013/01/towards-bayesian-morse-decoder.html >>> http://ag1le.blogspot.com/2013/02/probabilistic-neural-network-classifier.html >>> http://ag1le.blogspot.com/2012/05/morse-code-decoding-with-self.html >>> >>> >>> My questions are related to NuPIC and how could I start testing whether CLA >>> algorithm would perform better than the currently used Bayesian algorithm? >>> >>> The challenges I see after studying the NuPIC documentation & example code: >>> >>> 1) How to create encoder for building sparse representation from audio >>> signals? (some ideas here: >>> http://ag1le.blogspot.com/2014/05/sparse-representations-of-noisy-morse.html >>> ) >>> >>> 2) If you teach NuPIC CLA to recognize Morse character set as sequence of >>> "mark" / "space" bit patterns, how can you decode apparently random bit >>> patterns from spatial pooler back to ASCII character set to be displayed to >>> user? Does any of the existing classifiers allow users to create their own >>> "codebook" (see >>> http://ag1le.blogspot.com/2012/05/fldigi-adding-matched-filter-feature-to.html >>> example using Kohonen Self Organizing Maps to build a codebook) >>> >>> 3) Does NuPIC CLA also recognize some common language patterns ("higher >>> order sequences") that are typically used in normal ham radio contacts ? Or >>> is there a need to chain multiple CLAs in some sort of hierarchy? >>> >>> regards, >>> Mauri AG1LE >>> >>> >>> >>> >>> >>> _______________________________________________ >>> nupic mailing list >>> [email protected] >>> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >>> >> >> >> >> -- >> >> Chris Albertson >> Redondo Beach, California >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org _______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
