| 查看: 800 | 回复: 5 | ||||
| 当前主题已经存档。 | ||||
| 当前只显示满足指定条件的回帖，点击这里查看本话题的所有回帖 | ||||
zzbei木虫 (正式写手)
|
[交流]
自适应matlab程序（LMS和RLS）
|
|||
|
%lms算法源程序 clear all close all %channel system order sysorder = 5 ; % Number of system points N=2000; inp = randn(N,1); n = randn(N,1); [b,a] = butter(2,0.25); Gz = tf(b,a,-1); %This function is submitted to make inverse Z-transform (Matlab central file exchange) %The first sysorder weight value %h=ldiv(b,a,sysorder)'; % if you use ldiv this will give h :filter weights to be h= [0.0976; 0.2873; 0.3360; 0.2210; 0.0964;]; y = lsim(Gz,inp); %add some noise n = n * std(y)/(10*std(n)); d = y + n; totallength=size(d,1); %Take 60 points for training N=60 ; %begin of algorithm w = zeros ( sysorder , 1 ) ; for n = sysorder : N u = inp(n:-1:n-sysorder+1) ; y(n)= w' * u; e(n) = d(n) - y(n) ; % Start with big mu for speeding the convergence then slow down to reach the correct weights if n < 20 mu=0.32; else mu=0.15; end w = w + mu * u * e(n) ; end %check of results for n = N+1 : totallength u = inp(n:-1:n-sysorder+1) ; y(n) = w' * u ; e(n) = d(n) - y(n) ; end hold on plot(d) plot(y,'r'); title('System output') ; xlabel('Samples') ylabel('True and estimated output') figure semilogy((abs(e))) ; title('Error curve') ; xlabel('Samples') ylabel('Error value') figure plot(h, 'k+') hold on plot(w, 'r*') legend('Actual weights','Estimated weights') title('Comparison of the actual weights and the estimated weights') ; axis([0 6 0.05 0.35]) % RLS 算法 randn('seed', 0) ; rand('seed', 0) ; NoOfData = 8000 ; % Set no of data points used for training Order = 32 ; % Set the adaptive filter order Lambda = 0.98 ; % Set the forgetting factor Delta = 0.001 ; % R initialized to Delta*I 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 RLS P = Delta * eye ( Order, Order ) ; w = zeros ( Order, 1 ) ; % RLS Adaptation for n = Order : NoOfData ; u = x(n:-1:n-Order+1) ; pi_ = u' * P ; k = Lambda + pi_ * u ; K = pi_'/k; e(n) = d(n) - w' * u ; w = w + K * e(n) ; PPrime = K * pi_ ; P = ( P - PPrime ) / Lambda ; 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') ; [ Last edited by 幻影无痕 on 2006-10-26 at 07:47 ] |
回复此楼» 收录本帖的淘贴专辑推荐
 source |
» 猜你喜欢
刚刚收到科研之友邮件
已经有23人回复
-
切削液交流群
已经有5人回复
-
试用期辞职
已经有16人回复
-
面青地会评时间？？？
已经有8人回复
-
F03青年基金函评结果
已经有4人回复
-
青年基金会评专家到底是怎么会评的呀？主审专家是不是一般不会改动系统按函评给的顺序
已经有16人回复
-
关于读博感觉自己很抓马
已经有12人回复
-
投稿求助
已经有4人回复
-
工材口青年基金上会可能性
已经有10人回复
-
试剂价格
已经有5人回复
8