function [yn,err] = adjust(xn, dn, param)
%?x????????输入信号??
%?dn???????期望输出??
%?param????Structure?for?using?LMS,?must?include?at?least??
%??????????.w????????-?初始化权值??
%??????????.u????????-?学习率??
%??????????.M????????-?滤波器阶数??
%??????????.max_iter?-?最大迭代次数??
%??????????.min_err??-?迭代最小误差??
%??
%?y????????经过滤波器后的输出信号??
%?error????误差输出??
W = param.W; %?初始权值?
W = dsp.LMSFilter(xn)
M = param.M; %?滤波器阶数??
%?LMS自适应滤波??
param.M = 50;
param.W = ones(param.M, 1) * 0.1;
param.u = 0.1;
param.max_iter = 100;
param.min_err = 0.5;
if length(W) ~= M
error('param.w的长度必须与滤波器阶数相同.\n');
end
if param.max_iter > length(xn) || param.max_iter < M
error('迭代次数太大或太小，M<=max_iter<=length(xn)\n');
end
iter = 0;
for k = M:param.max_iter
x = xn(k:-1:k-M+1); %?滤波器M个抽头的输入??
y = W.*x;
err = dn(k) - y;
%?更新滤波器权值系数??
W = W + 2*param.u*x;
iter = iter + 1;
if (abs(err) < param.min_err); break; end
end
%?求最优时滤波器的输出序列??
yn = inf * ones(size(xn));
for k = M:length(xn)
x = xn(k:-1:k-M+1);
yn(k) = W(:,end).'* x;
end
end
