www.pudn.com > adaptivefiltering.rar > lms_eq.m

% lms_eq.m - use multidimensional LMS algorithm to estimate channel response 
% written for MATLAB 4.0 
% 
% Input parameters: 
%                Xi       : matrix of training/test points - each row is 
%                           considered a datum 
%                y        : desired vector output values corresponding to Xi 
%                verbose: set to 1 for interactive processing 
%                alpha    : the initial value of step size 
%                decay    : set to 1 for O(1/n) decay in alpha 
 
Nin  = size(Xi, 2); 
Nout = size(Y, 2); 
 
% maximum number of timesteps that can be predicted 
N = size(Xi, 1); 
 
% initialize weight matrix and associated parameters for LMS predictor 
W  = zeros(Nout, Nin); 
Wo = []; 
 
for n = 1:N, 
 
    % save weights 
    Wo = [Wo W']; 
  
    % predict next sample and error 
    xp(n, :) = Xi(n, :) * W'; 
    e(n, :)  =  Y(n, :) - xp(n, :); 
    ne(n) = norm(e(n, :)); 
    if (rp.verbose ~= 0)                                                                        
        disp(['time step ', int2str(n), ': mag. pred. err. = ' , num2str(ne(n)) ] );                                                      
    end; 
    % adapt weight matrix and step size 
    W = W + rp.mu * e(n, :)' * Xi(n, :); 
    if (rp.decay == 1) 
      rp.mu = rp.mu * n/(n+1); % use O(1/n) decay rate 
    end; 
end % for n