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
