A NuPIC novice myself, I suspect that to account for noise in the duration of a particular pattern, you would want to have a coarser grained aggregation of your input values when swarming. There are aggregation params in the model (although I can't remember ATM precisely what they're called). As long as the aggregation is mostly covering the noise, I think this would work.
Interestingly, in *How to Create a Mind*, Ray Kurzweil discusses the problem of variation in duration of an input pattern, using speech sounds as an example. His model is a bit different from CLA/HTM, and he models inputs with an expected range for the duration. On Tue, Apr 8, 2014 at 1:28 AM, Scheele, Manuel < [email protected]> wrote: > Hi all, > > I have been semi-successful with learning sequences and recognising noisy > versions of them using NuPIC. > > But now I am curious about something else. What if the noise is not in the > sequence values (i.e. [1, 3, 4] plus noise becomes [1.1, 2.9, 4.05]) but in > the 'time domain' (i.e. [1, 1, 2, 2, 5, 5, 5] plus noise becomes [1, 1, 1, > 2, 5, 5]) meaning where the transitions between sequence values are the > same but the 'time' spend in one sequence state varies? > > This happens, for example, when we speak: we we spend different amounts of > time in different parts of a word depending on the speed of our speech. > Does the TP deal with this? How can I see if NuPIC can deal with this sort > of problem and if so, how well? > > Regards, > Manuel > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >
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