加性噪声的小波去噪问题，效果不理想

songjie2895

下面是我自己的加噪（加的是高斯白噪声）和小波去噪程序,去噪效果不理想，大家帮我看看是不是我小波去噪的参数选择的不对，谢谢诸位了
clc;
close all;
clear all;

%源信号
p1=30;p2=50;           %frequencies of s1
p3=60;                 %frequencies of s2
SigLen=512;            %length of the sources
points=512;            %number of represented points
m=2;n=2;               %m为源数，n为观测信号数
s1=sin([1:SigLen]*p1*2*pi/SigLen)+sin([1:SigLen]*p2*2*pi/SigLen);     %源信号s1
s2=sin([1:SigLen]*p3*2*pi/SigLen);                                    %源信号s2
s=[s1;s2];             %源信号矩阵
for i=1:n
    s(i,:)=s(i,:)-mean(s(i,:));           %中心化（去均值)
    s(i,:)=s(i,:)/std(s(i,:));            %normalization of the source signals
end

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%观测信号
A11=1;A22=1;A12=-0.72222;A21=-0.59447;
A=[A11 A12;A21 A22];                      %混合矩阵A
X=A*s;                                    %观测信号X
subplot(3,2,1),plot(X(1,:),'MarkerEdgeColor','k','MarkerFaceColor','k');  %观测信号x1的图形
title('观测信号 1');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);
subplot(3,2,2),plot(X(2,:),'MarkerEdgeColor','k','MarkerFaceColor','k')   %观测信号x2的图形
title('观测信号 2');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);
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%noise on signal 1:
snr1=-30;                 %信噪比为-30db
X_noised(1,:)=zeros(1,length(X(1,:)));
X_noised(1,:)=awgn(X(1,:),snr1);
subplot(3,2,3),plot(X_noised(1,:),'MarkerEdgeColor','k','MarkerFaceColor','k');
title('加噪观测信号 1');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%noise on signal 2:
snr2=-20;                 %信噪比为-20db
X_noised(2,:)=zeros(1,length(X(2,:)));
X_noised(2,:)=awgn(X(2,:),snr2);
subplot(3,2,4),plot(X_noised(2,:),'MarkerEdgeColor','k','MarkerFaceColor','k');
title('加噪观测信号 2');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%对观测信号进行小波阈值消噪

X_denoised=zeros(n,SigLen);
TPTR_before='heursure';          %threshold selection rule
thresholding_before='s';         %阈值选择
Lev_before=2;                    %小波的分解层数
Wname='sym6';                    %wavelet basis

%对第一个含噪观测信号X_noised(1,:)进行小波阈值消噪

[xd,cxd,lxd]=wden(X_noised(1,:),TPTR_before,thresholding_before,'sln',Lev_before,Wname);
X_denoised(1,:)=xd;
subplot(3,2,5),plot(X_denoised(1,:),'MarkerEdgeColor','k','MarkerFaceColor','k');     %估计消噪后观测信号X_denoised1的图形
title('小波消噪后观测信号 1');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);

%对第二个含噪观测信号X_noised(2,:)进行小波阈值消噪

[xd,cxd,lxd]=wden(X_noised(2,:),TPTR_before,thresholding_before,'sln',Lev_before,Wname);
X_denoised(2,:)=xd;
subplot(3,2,6),plot(X_denoised(2,:),'MarkerEdgeColor','k','MarkerFaceColor','k');     %估计消噪后观测信号X_denoised2的图形
title('小波消噪后观测信号 2');
set(gca,'xlim',[0 points]),set(gca,'xtick',[0:points/4:points]);

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