homework4.m

ar模型 bt算法 ls rls lms music等数字信号处理的源代码

clear;
clc;
N1=1000;
N=512;
N2=100;
a1=input('please input a')
a2=input('please input a')
sigma_v2=input('please input the variance of v');
w=zeros(2,N,N2);
e=zeros(N2,N);
for k=1:N2
    v=sqrt(sigma_v2)*randn(1,N1);
    u1=zeros(1,N1);
    u1(1)=0;
    u1(2)=0;
    for m=1:N1-2
        u1(m+2)=-a1*u1(m+1)-a2*u1(m)+v(m);
    end
    u=u1(N1-N+1:N1);
    u2=[ 0 u];
    c=0.01;
    Jmin=0.005;
    K_n=c*eye(2);
    for n=1:N-1
        d=u2(n+2);
        x=[u2(n+1);u2(n)];
        A=x'*K_n*x+Jmin;
        G=K_n*x*inv(A);
        alfa=d-x'*w(:,n,k);
        w(:,n+1,k)=w(:,n,k)+G*alfa; 
        K_n=K_n-G*x'*K_n;
        e(k,n+1)=(d-(w(:,n+1,k))'*x).^2;
    end
end
w1=mean(w,3);
e1=mean(e);
plot(0:length(e1)-1,e1)
xlabel('迭代次数n')
ylabel('均方误差')