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From: ImageAnalyst <imageanalyst@mailinator.com>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Separated the noise
Date: Thu, 25 Dec 2008 20:42:47 -0800 (PST)
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On Dec 25, 11:13=A0pm, "Muhammad " <fahrudin_fis...@yahoo.com> wrote:
> dear who considering
>
> i write my simple code under my simple information of matlab function
> and post the code in order to benefit other beginner
> thanks
> I have a problem and I hope any help for me
>
> how to separated the original signal from its noise.
>
> I have a =A0wave(.wav)
> I blend it with noise.
> my listing program :
> y=3Dwavread(open.wav);
> spect=3Dabs(fft(y,1024));
> frek=3D linspace(0,22050,512)
> plot(frek,spect(1:512));
> % generate and mix the noise.
> open_noise=3Dagwn(y,20);
>
> Thank you.

-----------------------------------------------
Muhammed:
I don't know the function agwn().  What is it?
You could add the noise to your signal (y) and then use a Wiener
filter (in the image processing toolkit) to recover an estimate of
your signal.  Or you could try a median filter.  There are lots of
ways to reduce noise and try to recover your signal.  Each makes some
kind of assumption about the type of signal and noise, like the
spectrum or way the noise affects your signal (additive,
multiplicative, Gaussian, salt and pepper, 1/f, whether the noise
comes in before the point spread function takes effect or after,
etc.)  For example, if you have additive Gaussian noise, and a signal
presumed to be made up from a known function (e.g. a polymonial of
some order), then you can try a least squares fit.
Good luck,
ImageAnalyst