add ecgmalab

ecgmalab重新添加

基于机器学习的心电图诊断识别/心电数据预处理/ecgmalab/waveletdenoising.m

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+%*********************去除噪声和基线漂移*********************% 
+level=8; 
+wavename='bior2.6'; 
+ecgdata=M(:,1); 
+figure(2); 
+plot(ecgdata(1:points));grid on ;axis tight;axis([1,points,-2,5]); 
+title('原始ECG 信号'); 
+%%%%%%%%%%进行小波变换8 层 
+[C,L]=wavedec(ecgdata,level,wavename); 
+%%%%%%%提取近似系数， 
+A1=appcoef(C,L,wavename,1); 
+A2=appcoef(C,L,wavename,2);
+A3=appcoef(C,L,wavename,3); 
+A4=appcoef(C,L,wavename,4); 
+A5=appcoef(C,L,wavename,5); 
+A6=appcoef(C,L,wavename,6); 
+A7=appcoef(C,L,wavename,7); 
+A8=appcoef(C,L,wavename,8); 
+%%%%%%%提取细节系数 
+D1=detcoef(C,L,1); 
+D2=detcoef(C,L,2); 
+D3=detcoef(C,L,3); 
+D4=detcoef(C,L,4); 
+D5=detcoef(C,L,5); 
+D6=detcoef(C,L,6); 
+D7=detcoef(C,L,7); 
+D8=detcoef(C,L,8); 
+%%%%%%%%%%%%重构 
+A8=zeros(length(A8),1); %去除基线漂移,8 层低频信息 
+RA7=idwt(A8,D8,wavename); 
+RA6=idwt(RA7(1:length(D7)),D7,wavename); 
+RA5=idwt(RA6(1:length(D6)),D6,wavename); 
+RA4=idwt(RA5(1:length(D5)),D5,wavename); 
+RA3=idwt(RA4(1:length(D4)),D4,wavename); 
+RA2=idwt(RA3(1:length(D3)),D3,wavename); 
+D2=zeros(length(D2),1); %去除高频噪声，2 层高频噪声 
+RA1=idwt(RA2(1:length(D2)),D2,wavename); 
+D1=zeros(length(D1),1);%去除高频噪声，1 层高频噪声 
+DenoisingSignal=idwt(RA1,D1,wavename); 
+figure(3); 
+plot(DenoisingSignal); 
+title('去除噪声的ECG 信号'); grid on; axis tight;axis([1,points,-2,5]); 
+clear ecgdata;