% 用小波(包)对MitbihCmprTstExample_08730_01(软硬阈值)进行消噪与压缩

clear all;clc;close all;

disp('用小波(包)对MitbihCmprTstExample_08730_01(软硬阈值)进行消噪和压缩');

load MitbihCmprTstExample_08730_01.mat;

count=length(sig);

x=sig(:,1); y=sig(:,2); z=sig(:,3);

TS=x(2)-x(1); Freq=1/TS; % 心博周期和频率

% 画出原始信号

subplot(3,2,1),plot(y),title('原始信号'),grid;

%用db1小波对原始信号进行3层分解并提取系数

[c,l]=wavedec(y,3,'db1');

ca3=appcoef(c,l,'db1',3); % 1-D approximation coefficients一维近似系数

cd3=detcoef(c,l,3); %提取第3层细节系数;1-D detail coefficient

cd2=detcoef(c,l,2); %提取第2层细节系数

cd1=detcoef(c,l,1); %提取第1层细节系数

% 对信号进行强制去噪

cdd3=zeros(length(cd3),1);

cdd2=zeros(length(cd2),1);

cdd1=zeros(length(cd1),1);

c1=vertcat(ca3,cdd3,cdd2,cdd1); % 垂直方向的矩阵连接

y1=waverec(c1,l,'db1');

subplot(3,2,2),plot(y1),grid;

axis([0 5000 -1 1]);

title('强制去噪后的信号');

% 用默认阈值对信号进行去噪

[thr, sorh, keepapp] = ddencmp('den','wv',y);%获得信号的默认阈值

[y2,CXC,LXC,PERF0,PERFL2] =wdencmp('gbl',c,l,'db1',3,thr,sorh,keepapp);%---perf0=80.4

% y2=wdencmp('gbl',c,l,'db1',3,thr,sorh,keepapp);

subplot(3,2,3),plot(y2),grid;

axis([0 5000 -1 1]);

title('用默认阈值去噪后的信号');

% 用给定的软阈值进行去噪

cd1soft=wthresh(cd1,'s',1.465);

cd2soft=wthresh(cd2,'s',1.823);

cd3soft=wthresh(cd3,'s',2.768);

c2=vertcat(ca3,cd3soft,cd2soft,cd1soft);

y3=waverec(c2,l,'db1');

subplot(3,2,4),plot(y3),grid;

axis([0 5000 -1 1]);

title('用软阈值去噪后的信号');

% 用默认阈值对信号进行(小波)压缩

[thr_cmp,sorh_cmp,keepapp_cmp] = ddencmp('cmp','wv',y);

[y4,CXC_cmp,LXC_cmp,PERF0_cmp,PERFL2_cmp] = wdencmp('gbl',c,l,'db1',3,thr_cmp,sorh_cmp,keepapp_cmp);

%---PERF0_cmp=32.66

subplot(3,2,5),plot(y4),grid,axis([0 5000 -1 1]);

title('用默认阈值进行小波压缩');

%%

%用默认阈值对信号进行小波(包)压缩

% [thr_cmp2,sorh_cmp2,keepapp_cmp2,crit_cmp2] = ddencmp('cmp','wp',y);

% [y5,TREED_cmp2,PERF0_cmp2,PERFL2_cmp2] = ...

% wpdencmp(y,sorh_cmp2,3,'db1',crit_cmp2,thr_cmp2,keepapp_cmp2);

% %---PERF0_cmp2=37.62

% subplot(3,2,6),plot(y5),grid,axis([0 5000 -1 1]);

% title('用默认阈值进行小波包压缩');

% 这与采用默认阈值进行小波压缩效果非常接近