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Thread Subject:
An issue with using Wiener filter as a predictor

Subject: An issue with using Wiener filter as a predictor

From: Baran

Date: 25 Sep, 2013 04:15:59

Message: 1 of 2

hi

In Wiener filter w_opt=inv(R)*P'. where p is the cross-correlation between desired and the input signals. So in the case of prediction, when I am trying to model a multi-input single output system, do I need to reshape the input to a M by N matrix with M as the lag to predict the one-step ahead data? do I need to precisely define the desired output for each column of the reshaped time series in the input?

And the most important question, what should I do when I MATLAB xcorr function forces both argument to be of the same size? In fact, I am trying to calculate E{d(n).[x(n) x(n-1)...x(n-M+1)]'}, but I cannot do that by xcorr.

any help is so appreciated

Subject: An issue with using Wiener filter as a predictor

From: Greg Heath

Date: 14 Oct, 2013 21:01:05

Message: 2 of 2

Baran <andalibar@gmail.com> wrote in message <dba3de0d-0424-40e5-9329-daed91d527b2@googlegroups.com>...
> hi
>
> In Wiener filter w_opt=inv(R)*P'. where p is the cross-correlation between desired and the input signals. So in the case of prediction, when I am trying to model a multi-input single output system, do I need to reshape the input to a M by N matrix with M as the lag to predict the one-step ahead data? do I need to precisely define the desired output for each column of the reshaped time series in the input?
>
> And the most important question, what should I do when I MATLAB xcorr function forces both argument to be of the same size? In fact, I am trying to calculate E{d(n).[x(n) x(n-1)...x(n-M+1)]'}, but I cannot do that by xcorr.
>
> any help is so appreciated

I am no longer familiar with Wiener Filters. However, to use correlation functions, zero-pad the shorter vectors.

Hope this helps.

Greg

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