lms.m

LMS自适应算法

clear all;
close all;
% LMS算法验证
ChouTou = 11;              %抽头
AveTime = 500;             %平均次数      
N = 1008;                % 输入噪声序列长度与迭代次数有关
mu = 0.075;

% 冲击函数
n = [1:3]';
w = [2.9,3.1,3.3,3.5]';
Hn = zeros(length(n),length(w));
for i = 1:length(w)
    Hn(:,i)= 0.5*(1+cos(2*pi*(n-2)/w(i)));
end

OverLap = N+length(n)-ChouTou;
W1 = zeros(ChouTou,(OverLap+1));%权列向量 初始状态多算一次
W2 = zeros(ChouTou,(OverLap+1));%权列向量 初始状态多算一次
W3 = zeros(ChouTou,(OverLap+1));%权列向量 初始状态多算一次
W4 = zeros(ChouTou,(OverLap+1));%权列向量 初始状态多算一次
kesai1=zeros(OverLap,1);
kesai2=zeros(OverLap,1);
kesai3=zeros(OverLap,1);
kesai4=zeros(OverLap,1);
Delay = 7;

for i = 1:length(w)
    for AT = 1:AveTime
        P = 2000;
        Noise1 = randsrc(P,1);    % 产生波努力噪声序列
        W = zeros(ChouTou,(OverLap+1));
        kesai = zeros(OverLap,1);
        X1n = Noise1(100:(100+N-1));
        Dn = Noise1((100+ChouTou-Delay):(100+OverLap+ChouTou-Delay));
        X2n = conv(X1n,Hn(:,i))+sqrt(0.001)*randn(N+length(Hn(:,i))-1,1);
        
        for k = 1:OverLap  % length(X2n)-ChouTou+1次迭代
            X = flipud(X2n(k:(k+ChouTou-1)));
            kesai(k) = Dn(k)-X'*W(:,k);
            W(:,k+1) = W(:,k)+mu*kesai(k)*X;
        end
        
        if i == 1
            W1 = W1+W;
            kesai1 = kesai.^2+kesai1;
        end
        if i == 2;
            W2 = W2+W;
            kesai2 = kesai.^2+kesai2;
        end
        if i == 3
            W3 = W3+W;
            kesai3 = kesai.^2+kesai3;
        end
        if i == 4;
            W4 = W4+W;
            kesai4 = kesai.^2+kesai4;
        end
    end
end

figure(1)
subplot(4,1,1);
stem(W1(:,OverLap+1)/AveTime);
ylabel('权值(w=2.9)','Fontsize',12),
title('权系数解','Fontsize',14),
subplot(4,1,2);
stem(W2(:,OverLap+1)/AveTime);
ylabel('权值(w=3.1)','Fontsize',12),
subplot(4,1,3);
stem(W3(:,OverLap+1)/AveTime);
ylabel('权值(w=3.3)','Fontsize',12),
subplot(4,1,4);
stem(W4(:,OverLap+1)/AveTime);
xlabel('k','Fontsize',12),
ylabel('权值(w=3.5)','Fontsize',12),

        
 figure(2)
 semilogy(1:length(kesai1),kesai1/500);
 hold on
 semilogy(1:length(kesai2),kesai2/500);
 hold on
 semilogy(1:length(kesai3),kesai3/500);
 hold on
 semilogy(1:length(kesai4),kesai4/500);
 xlabel('Number of iterations');
 ylabel('Ensemble-average square error');
 title('自适应信道均衡的LMS算法(500次平均)');