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% LMS Algorithm
% Written By: Sundar Sankaran and A. A. (Louis) Beex
% DSP Research Laboratory
% Dept. of Electrical and Comp. Engg
% Virginia Tech
% Blacksburg VA 24061-0111
randn('seed', 0) ;
rand('seed', 0) ;
NoOfData = 8000 ; % Set no of data points used for training
Order = 32 ; % Set the adaptive filter order
Mu = 0.01 ; % Set the step-size constant
x = randn(NoOfData, 1) ;% Input assumed to be white
h = rand(Order, 1) ; % System picked randomly
d = filter(h, 1, x) ; % Generate output (desired signal)
% Initialize LMS
w = zeros(Order,1) ;
% LMS Adaptation
for n = Order : NoOfData
D = x(n:-1:n-Order+1) ;
d_hat(n) = w'*D ;
e(n) = d(n) - d_hat(n) ;
w = w + Mu*e(n)*D ;
w_err(n) = norm(h - w) ;
end ;
% Plot results
figure ;
plot(20*log10(abs(e))) ;
title('Learning Curve') ;
xlabel('Iteration Number') ;
ylabel('Output Estimation Error in dB') ;
figure ;
semilogy(w_err) ;
title('Weight Estimation Error') ;
xlabel('Iteration Number') ;
ylabel('Weight Error in dB') ;