lms.m

A simple code for understanding lms nlms and wiener filters for beginners

function [MSE,W]=lms(mu,N,u,d);


% Input arguments:
% mu = step size, dim 1x1
% M = filter length, dim 1x1
% u = input signal, dim Nx1
% d = desired signal, dim Nx1
%
% Output arguments:
% e = estimation error, dim Nx1
% w = final filter coefficients, dim Mx1

w=zeros(N,1);
M=length(u);
u=u(:);
d=d(:);
W=[];
%LMS starts here
for n=N:M
    uvec=u(n:-1:n-N+1);
    e(n)=d(n)-w'*uvec;
    w=w+mu*uvec*conj(e(n));
    W=[W w];
    E(n) = e(n);
    MSE(n) = mean(E(1:n));
end
figure(1);
plot(MSE);grid on;