Hi Patrick,

Yes the input data is flowing at the same rate of the prediction. The
number of bits is "flexible" since each single bit has full semantic
meaning (both for the input and the prediction). I dont know if feeding the
data in the TP will be good idea (it will require a very large chunk of
data to be fee.. and probably the prediction could too far in the
future.... ). Probably, i could need something smaller and the the SP will
be required. We will see... :-)




2013/8/6 Patrick Higgins <[email protected]>

> Hi Valentin,
>
> 1. How many bits long is one set of data from your
> source? What I mean by 'one set' is a complete
> group or record of 0s and 1s from each of the
> independent places that report an output before
> the sequence repeats.
>
> 2. How quickly will each record become available?
>
>
> I'm hearing you say you want to feed the data
> into the TP directly, but I don't see how that can
> work. You'll need to send it thru the front end of
> the CLA so it can first run your data thru the SP
> first and those patterns will then be fed to the TP.
>
> Your data sounds sparse enough for the CLA
> to work with. I'd start by feeding your raw data
> into the CLA as records and experiment with
> the setting until you find its able to learn the
> patterns and accurately predict the next record.
> If your data has semantic meaning and you have
> a fast paced changing set of data, then the CLA
> should be able to find patterns and make predictions.
>
>
>
>
> Patrick
>
>
>
>
>
> On Aug 6, 2013, at 2:08 PM, Valentin Puente wrote:
>
> > That was my idea: the encoding it is a complex task to it in HW. I think
> the TP and SP are doable (especially if you use non-volatile memory
> devices).
> >
> > My approach was to use the examples of the temporal pooler as start
> point (nupic/examples/tp/). Do you think that it could easier to start from
> the "real thing" and just bypass internally the encoding? I'm a bit lost
> here :-)
> >
>
>
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