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From: adi cohen on 13 Jul 2010 10:32
"Matt J " <mattjacREMOVE(a)THISieee.spam> wrote in message <i1hqdm$p7r$1(a)fred.mathworks.com>...
> "adi cohen" <kerenpur(a)yahoo.com> wrote in message <i1hodp$inp$1(a)fred.mathworks.com>...
>
> > In order to restore it but maintain the shape of the signal as much as possible, what is the best approach?
> ==============
>
> That really depends on what you know in advance about the signal and the process that corrupts it. Since you're considering a wiener filter, it presumably means the signal is WSS and the corruption of the signal is additive noise, also WSS.
>
> > I thought about using a wiener filter, but cannot find a function in matlab
> > that filters one-dimentional signals using the wiener algorithm
> =================
>
> If you have the Image Processing Toolbox, you could probably use deconvwnr(). Even if your signal is 1-dimensional, you could just pretend that it's a 1-dimensional image.

thank you,
I want to assum that the signal is WSS and that the noise is added, WSS as well. But the wiener filter ruins the shape of the my signal...is there a filter that does a better job at maintaining the shape?
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