2.改变步长后的自相关谱.m

自适应谱线增强问题

clear;
clc;

Fi=2*pi*rand(1,1);                  % 产生随机相位Fi
X1=[];
for n=1:20000                       % 产生信号序列X1(n)
    x=sin(0.05*pi*n+Fi);
    X1=[X1;x];
end

V=randn(30002,1);                   % 产生白噪声序列V(n)
X2=[];
for n=1:30000                       % 产生信号序列X2(n)
    x=V(n+2)+2*V(n+1)+V(n);
    X2=[X2;x];
end
X2=X2(10001:30000);
X=X1+X2;

Y=[linspace(0,0,10000)];
E=[linspace(0,0,10000)];
H=[0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0; 0];   % 初始滤波器系数H(0)
T=H';
e=0;
for n=10001:19999
    Y(n-10000)=H'*[X(n-100);X(n-101);X(n-102);X(n-103);X(n-104);X(n-105);X(n-106);X(n-107);X(n-108);X(n-109);X(n-110);X(n-111);X(n-112);X(n-113);X(n-114);X(n-115);X(n-116);X(n-117);X(n-118);X(n-119)];
    E(n-10000)=X(n+1)-Y(n-10000);   % 计算每步误差e(n+1)
    H=H+0.00001*E(n-10000)*[X(n-100);X(n-101);X(n-102);X(n-103);X(n-104);X(n-105);X(n-106);X(n-107);X(n-108);X(n-109);X(n-110);X(n-111);X(n-112);X(n-113);X(n-114);X(n-115);X(n-116);X(n-117);X(n-118);X(n-119)];
    T=[T; H'];                      % 计算每步滤波器系数H(n+1)
end
YY=xcorr(Y,'unbiased');
EE=xcorr(E,'unbiased');
figure(1)
plot(YY(9901:10100))
figure(2)
plot(EE(9901:10100))