基于MATLAB的LMS和RLS算法滤波完整程序

基于MATLAB的LMS和RLS算法滤波完整程序，一种是LMS算法，一种是RLS算法，并在MATLAB环境下对其进行了编程.对自适应滤波器性能进行分析

%LMS自适应滤波器性能分析 
clear 
clc
close all
%%%%%%%%%%%%%%参数设置%%%%%%%%%%%%%%%%%%%%%%%
w=3;
% step_len=0.075;%步长
step_len=0.05;%步长

variance_v=0.01;%方差
repeat_times=20;%重复次数
iteration_times=500;%迭代次数
filt_len=2;%滤波器长度
delay=fix（filt_len/2）-1;
delay1=1;



%%%%%%%%%%%%%%%%%%%%变量及数组初始化%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Chan_factor=（1+cos（2*pi*（[1:1:3]-2）/w））/2
Square_err=zeros（repeat_timesiteration_times）;
% Chan_factor1=[-0.195 0.95]
Chan_factor1=[-0.195 0.95]
X=zeros（filt_len1）;
W1=[];
W2=[];
Wm1=[repeat_timesiteration_times];
Wm2=[repeat_timesiteration_times];


%%%%%%%%%%%%%外循环，重复做repeat_timws次实验，平均值%%%%%%%%%%%%%%%%

for loop1=1:repeat_times%循环次数
    
%%%%%%%%%%%%%%内循环变量及数组初始化%%%%%%%%%%%%%%%%%%%%%%%%
Source=zeros（iteration_times1）;
W=zeros（filt_len1）;

%%%%%%%%%%%%%内循环，做iteration_times次迭代%%%%%%%%%%%%%%%%%%%%%%%%%%%%
   for i=1:iteration_times
%%%%%%%%%%%%%%信源，产生等概率分布的正负1%%%%%%%%%%%%%%%%%%%%%%%%%%%%
      if rand<0.5
          Source（i）=-1;
      else
          Source（i）=1;
      end
   end
%%%%%%%%%%%%%%信道，滤波和加噪声%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 Revdata=filter（Chan_factor11Source）+randn（iteration_times1）*sqrt（variance_v）;
%  Revdata=filter（Chan_factor1Source）+randn（iteration_times1）*sqrt（variance_v）;  
%    Revdata=filter（Chan_factor11Source）;
   
% RT=filter（Chan_factor11Source）;
%%%%%%%%%%%%%%均衡器，基于LMS算法%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    
    for loop2=1:iteration_times-filt_len+1
        
%         U=Revdata（loop2:loop2+filt_len-1）;
%          y（n）=W‘*U=W‘*x（n）U=x（n）=输入
%          d为输出
        U=Source（loop2:loop2+filt_len-1）;
        d=Revdata（loop2+1）;
%         d=Source（loop2+delay）;
%         X= x（3）=v（3）-a1*x（2）-a2*x（1）;
        
%           d=RT（loop2+delay1）;
%         Y（loop2）=W‘*U;
        e=d-W‘*U;
%         e=d-W‘*U;
        W=W+step_len*U*e;
        
        Wm1（loop2loop1）=W（1）;
        Wm2（loop2loop1）=W（2）;
%         W1（loop2）=W（1）;
%         W2（loop2）=W（2）;
        Square_err（loop1loop2）=e.^2;
    end
    
    
end



%%%%%%%%%%%%%%作图，显示结果%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Square_err_mean=sum（Square_err（::））/repeat_times;
% Wm2
W1=Wm1（:repeat_times）;
W2=Wm2（:repeat_times）;
meanW1=mean（Wm1‘）;
meanW2=mean（Wm2‘）;
Square_err;
%semilogy（Square_err_mean）;
figure（1）;
plot（Square_err_mean）;
hold on;
plot（Square_err（1:）‘r‘）;
legend（‘20次重复试验平均误差‘‘单次误差‘）;
xlabel（‘迭代次数‘）;
ylabel（‘均方误差‘）;
title（‘步长为0.075，500次迭代均方误差变化曲线‘）;
grid on;
hold on;

figure（2）;
plot（W1）;
hold on;
plot（W2‘r‘）;
hold on;
plot（meanW1‘k‘）;
hold on;
plot（meanW2‘--k‘）;
legend（‘W1‘‘W2‘‘20次重复试验W1‘‘20次重复试验W2‘）;
xlabel（‘迭代次数‘）;
ylabel（‘抽头权值‘）;
title（‘步长为0.075，500次迭代权值学习曲线‘）;
grid on;

 属性            大小     日期    时间   名称
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     文件       2939  2017-12-17 16:08  LMS滤波程序.m

     文件       2731  2017-12-17 16:09  RLS滤波程序.m

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