jens
b31f3e7435
git-svn-id: http://moon:8086/svn/matlab/trunk@153 801c6759-fa7c-4059-a304-17956f83a07c
61 lines
1.7 KiB
Matlab
Executable File
61 lines
1.7 KiB
Matlab
Executable File
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% %
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% Fast LMS Algorithm %
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% %
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% Written By: Sundar Sankaran and A. A. (Louis) Beex %
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% DSP Research Laboratory %
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% Dept. of Electrical and Comp. Engg %
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% Virginia Tech %
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% Blacksburg VA 24061-0111 %
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% %
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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randn('seed', 0) ;
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rand('seed', 0) ;
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NoOfData = 8000 ; % Set no of data points used for training
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M = 32 ; % Set the adaptive filter order
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Mu = 0.01 ; % Set the step-size constant
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Gamma = 0.9 ; % Forgetting factor
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Delta = 0.01 ; % R_est initialized to Delta*I
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u = randn(NoOfData, 1) ;% Input assumed to be white
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h = rand(M, 1) ; % System picked randomly
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d = filter(h, 1, u) ; % Generate output (desired signal)
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% Initialize fast-lms
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W = zeros(2*M,1) ;
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p = Delta*ones(2*M,1) ;
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y = zeros(M, 1) ;
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e = zeros(M, 1) ;
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for k = 2 : floor(length(u)/M) - 1 ;
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U = fft(u((k-1)*M:(k+1)*M-1)) ;
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Y = ifft(U.*W) ;
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y(k*M:(k+1)*M-1) = real(Y(M+1:2*M)) ;
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e(k*M:(k+1)*M-1) = d(k*M:(k+1)*M-1) - y(k*M:(k+1)*M-1) ;
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E = fft([zeros(M,1); e(k*M:(k+1)*M-1)]) ;
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p = Gamma*p+(1-Gamma)*abs(U).^2 ;
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p_inv = 1./p ;
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PHI = ifft(p .* conj(U) .* E) ;
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phi = real(PHI(1 : M )) ;
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W = W + Mu / (2*M) * fft([phi; zeros(M,1)]) ;
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end ;
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% Plot results
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figure ;
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plot(20*log10(abs(e))) ;
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title('Learning Curve') ;
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xlabel('Iteration Number') ;
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ylabel('Output Estimation Error in dB') ;
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