[nengo-user] using nengo for linear or nonlinear regression

[Mansoureh Fahimi]

Hello nengo community,

I am trying to implement nengo to perform a simple linear ar regression of
order 1. for this I have an input time series, and I want to find the
parameters c and phi for the following equation: x(t)=c+phi*x(t-1)+e where
e is gaussian noise. There are numerous ways to solve this problem, but I
am curious as to how the Neural Engineering Framework can be applied to
solve this equation for a given time series.

As far as I have understood, this is implemented as a simple integrator
plus an unknown constant input (c)  in nengo where the transform weight is
also unknown (phi). But I can't figure out how it goes from hereon. is
there a paper with a similar problem you can refer me to?

I appreciate your help in advance.
Sincerely,

Mansoureh Fahimi
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