pjh3.m

PSD using BT/AR/ method,get the auto-correlation funtion

%LMS algorithm
close all;
clear all;
N1=1000;	      %总点数
N2=512;           %采样点数
K=100;            %循环次数
w0=zeros(1,2);
J_N2=0;
sum=zeros(1,N2);  %for learning curve
uu=0.005;          %parameter in one case
a1=-1.595;
a2=0.95;
var_v=0.0332;
y1=1.818;
y2=0.182;
%get the input data:u(n),n=1,2,...,N2
for nn=1:K        %循环K＝100次
  x=zeros(1,N1);
  u=zeros(1,N2);
  V=sqrt(var_v)*randn(1,N1);
  for n=3:N1
    x(n)=-a1*x(n-1)-a2*x(n-2)+V(n);%get the input data:u(n),n=1,2,...,N2
  end
  u=x(N1-N2+1:N1);  %选取后面N2个点
  clear x V;
  w1=zeros(1,N2);   %初始化w1,w2,e
  w2=zeros(1,N2);
  e=zeros(1,N2);
  e(1)=u(1);        %对e(1),e(2)初始化
  e(2)=u(2);
  w1(3)=uu*u(1)*u(2); %how??
  for m=3:N2
    e(m)=u(m)-conj(w1(m))*u(m-1)-conj(w2(m))*u(m-2);
    w1(m+1)=w1(m)+uu*conj(e(m))*u(m-1);
    w2(m+1)=w2(m)+uu*conj(e(m))*u(m-2);
  end
  sum=sum+abs(e).^2;
  J_N2=J_N2+abs(e(N2))^2;
  w0=w0+[w1(N2),w2(N2)];
end
sum=sum./K;         %学习曲线
w0=w0./K            %估计权向量
J_N2=J_N2/K;        %均方误差
Jex_N2=J_N2-var_v   %剩余均方误差
M=uu*(y1+y2)/(2-uu*(y1+y2))
ex_jinfi=M*var_v     %what??
est_M=Jex_N2/var_v   %失调
z=1:N2;
plot(z,sum);
grid on;
title('learning curve');
xlabel('n');
ylabel('估计均方误差');