Hi Gid, thanks for your questions. Please see:

- https://www.youtube.com/watch?v=KuFfm3ncEwI
-
https://github.com/rhyolight/nupic.examples/blob/master/sine-prediction/sine_experiment.py
-
http://lists.numenta.org/pipermail/nupic_lists.numenta.org/2013-June/000327.html

Also, since you are interested in what seems like audio processing, a lot
of us have done this type of work. Check out:

- https://github.com/nupic-community/nupic.audio
- https://github.com/nupic-community/nupic.critic
-
https://www.youtube.com/watch?v=y_hfUF1-ID8&index=12&list=PL3yXMgtrZmDpDhDZvixTUubv9R9cpZK4T

---------
Matt Taylor
OS Community Flag-Bearer
Numenta

On Tue, Jan 12, 2016 at 12:55 PM, gideon isaac <[email protected]> wrote:

> I had ideas for a application of nupic technology.  But first, I need to
> know a few things.
>
> HTM currently learns sequences.   So:
> Can it learn a sine wave, given that HTM neurons are just on and off?
>
> A sine wave is a smooth curve, and if I were to represent it with my own
> binary code, I would use two numbers (all numbers can be expressed in
> base-2 as binary) – one would be the amplitude (y-axis) and one would be
> the angle (x-axis).  But I doubt sparse representations would represent it
> that way.
>
> Secondly, sine waves go on forever.  Would HTM predictions be affected by
> that?
>
> There is a cell phone application that recognize tunes.  You hum it into
> the cell phone, and it tells you what the tune is.  Obviously the
> frequencies in a taune are more complex than just a sine wave – they vary
> in phase and frequency, and there are several frequencies occurring
> together, and then some stop, others start.   Would this overwhelm HTM?
>
> The above is actually not what I want to work on, (since it has been done
> already, though not with nupic) but it is related to the idea I have.
>
> Yet more questions, taking this tune-recognition application further:
> 1)
> Perhaps you would need several levels of regions, the lowest that would
> tease out the basic frequencies, and a higher one that would put them
> together again?
> 2)
> Also, if you were to associate a song title with the song, that raises a
> whole new question.  Suppose I have 2 regions.  One is presented with the
> title.  The other is presented, over time, with the tune.  Both feed into
> an upper layer, and the upper layer has feedback to the lower layers.
> Would that setup associate a song title with a tune?
> The same issue would be for learning language in general.  If you learn a
> word, it is just an arbitrary set of sounds associated with a concept.  So
> you would have to feed the word to one region, the concept to another, and
> somehow they would have to communicate.
>
> Thanks in advance
> Gid
>

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