matlab-小波分解与重构-滤波(共3页)

1、精选优质文档-倾情为你奉上m=load(A.txt);N=length(m);for i=1:N-1 ;q(i,1)=m(i,1); end;d=q;s1=d;change=1000;c,l = wavedec(d,3,db4);%提取小波分解后的低频系数ca3=appcoef(c,l,db4,3);%提取各层小波分解后的高频系数cd3=detcoef(c,l,3);cd2=detcoef(c,l,2);cd1=detcoef(c,l,1);%对信号强制消噪cdd3=zeros(1,length(cd3);%第三层高频系数cd3全置0cdd2=zeros(1,length(cd2);%第二层高

2、频系数cd2全置0cdd1=zeros(1,length(cd1);%第一层高频系数cd1全置0c1=ca3,cdd3,cdd2,cdd1;%构建新的系数矩阵s2=waverec(c1,l,db4)%分解新的结构%thr,sorh,keepapp=ddencmp(den,wv,d);%s2=wdencmp(gbl,c,l,db4,4,thr,sorh,keepapp);%subplot(413)%plot(1:change,s2(1:change);%title(默认软阈值消噪后信号)figure(1)subplot(9,2,1)plot(1:change,s1(1:change)title(

3、原始信号)ylabel(S1)subplot(9,2,2)plot(1:change,s2(1:change)title(强制消噪后信号)ylabel(S2)wpt=wpdec(s1,3,db1,shannon);%plot(wpt);%重构第三层8个节点小波系数s130=wprcoef(wpt,3,0);s131=wprcoef(wpt,3,1);s132=wprcoef(wpt,3,2);s133=wprcoef(wpt,3,3);s134=wprcoef(wpt,3,4);s135=wprcoef(wpt,3,5);s136=wprcoef(wpt,3,6);s137=wprcoef(w

4、pt,3,7);%计算第三层8个节点小波能量s10=norm(s130);s11=norm(s131);s12=norm(s132);s13=norm(s133);s14=norm(s134);s15=norm(s135);s16=norm(s136);s17=norm(s137);%计算方差st10=std(s130);st11=std(s131);st12=std(s132);st13=std(s133);st14=std(s134);st15=std(s135);st16=std(s136);st17=std(s137);disp(正常信号的特征向量);snorm1=s10,s11,s1

5、2,s13,s14,s15,s16,s17;std1=st10,st11,st12,st13,st14,st15,st16,st17;%显示三层个节点小波系数subplot(9,2,3);plot(1:change,s130(1:change);ylabel(S130);subplot(9,2,5);plot(1:change,s131(1:change);ylabel(S131);subplot(9,2,7);plot(1:change,s132(1:change);ylabel(S132);subplot(9,2,9);plot(1:change,s133(1:change);ylabel(S133);subplot(9,2,11);plot(1:change,s134(1:change);ylabel(S134);subplot(9,2,13);plot(1:change,s135(1:change);ylabel(S135);subplot(9,2,15);plot(1:change,s136(1: