lms.txt

lms算法的MATLAB的仿真程序

%
% Basic LMS EQ
% For real (I-axis) signals only
%

itn = 1e3; % # of data samples

sigman2 = .001; %noise variance (=1/SNR)
sigman=sqrt(sigman2);
ch = [-.1 .3 -.7 2 2 -.7 .3 -.1];  % channel coefficients

N = 8; %number of taps

mu=.01; % step size

runs = 1;  % number of independent triels to
xi=zeros(itn,1);

tic

for k=1:runs
    x=randint(itn,1)*2-1;
    d=filter(ch,1,x)+sigman*randn(itn,1);
    weights=zeros(N,1);
    for n=N:itn;
        xtdl=x(n:-1:n-N+1);
        e=d(n)-weights'*xtdl;
        weights=weights+mu*e*xtdl;
        xi(n)=xi(n)+e^2;
    end
end

toc

xi=xi/runs;
semilogy(xi)
xlabel('No. of iterations')
ylabel('MSE') 
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