Least Mean Square for System Identification

版本 1.0.0.0 (2.5 KB) 作者: Santhana Raj
Least Mean Square (LMS) used for system identification.
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更新时间 2014/9/10

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Least mean squares (LMS) algorithms are a class of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal).
The weights update Formula for every Iteration is Wt new=Wt old + mu * error *input;
For Example:
inp=wavread('BlueFunk-bass1.wav');
inp=inp-(min(inp)); % required for audio signals
h=[1 -4 6 -5 2]; % Known System papametes for a low Pass filter h
Iter=lms(inp,h,100,5,1);

Author:Santhana Raj.A https://sites.google.com/site/santhanarajarunachalam/

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Santhana Raj (2025). Least Mean Square for System Identification (https://ww2.mathworks.cn/matlabcentral/fileexchange/47790-least-mean-square-for-system-identification), MATLAB Central File Exchange. 检索时间: .

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1.0.0.0