Signal separation with Wiener filtering

Wiener filter estimation based on Wiener-Hopf equations for signal separation or denoising
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Updated 16 Feb 2020

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This function provides an implementation of the Wiener filter based on Wiener-Hopf equations.
Given a noisy signal and a reference signal, the Wiener filter can be applied to the noisy signal for estimating the contribution coherent with the reference signal.
Note that this kind of filter may be used also in cascade in order to separate multiple contribution if multiple references are present.
The function is provided with a demo in order to show its application in a simple case and it is full compatible with Octave.

% INPUTS
% x = noisy signal
% y = reference signalsinit
% N = filter order
%
% OUTPUTS
% xest = estimated signal
% b = Wiener filter coefficents
% MSE = mean squared error

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.2

The code has been improved: the function can be performed by using column or row vectors as inputs.

1.0.1

Title, summary, description and tags have been improved.

1.0.0