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下面temp3.m文件,数据文件sig5.txt (256点),运行x=temp3('sig5.txt'),即用同一数据源不同的小波处理,在我的机器上(MATLAB 2011a)得到的结果如图片.第二第三条曲线的结果太差,不正常.如果MATLAB Wavelet toolbox不能处理归范化信号,就是其Bug.

temp3.m

%Normalization changes results in Matlab toolbox?

%in Matlab 2011a.

function [x]=temp3(datafile)

close all force; Wavedata=load(datafile);

%size(Wavedata)

%Wavedata=sin(1:256); Wavedata=Wavedata(:)-mean(Wavedata(:)); x=bestwp(Wavedata,'db4',8);plot(x ,'or'); hold on;

x=bestwp(Wavedata,'sym35',8);plot(x ,'*b');

x=bestwp(Wavedata,'bior4.4',8);plot(x ,'+g'); Wavedata=Wavedata/norm(Wavedata(:));% Normalized x=bestwp(Wavedata,'db4',8);plot(x ,'xr');

x=bestwp(Wavedata,'sym35',8);plot(x ,'vb');

x=bestwp(Wavedata,'bior4.4',8);plot(x ,'sg'); legend('NotNormalized+db4','NotNormalized+sym35','NotNormalized+bior4.4','Normalized+db4','Normalized+sym35','Normalized+bior4.4','Location','SouthEast');

axis tight;

xlabel('Number of The Best Basis Coefficients in Descending Order (Absolute Value)');

ylabel('Coefficient Square Cumulation');

title([datafile ' Normalized or Not Before Wavelet Packet Decomposition']) ;

grid on;

%title(wavenum);

hold off

figure;plot(Wavedata);axis tight; title('Test Signal'); x=[];

end function [x]=bestwp(indata,wavenum,deps)

%dwtmode('ppd');

dwtmode('per'); T = wpdec(indata,deps,wavenum,'shannon');%,'log energy'); [bt,E,Nod] = besttree(T); %Nod = leaves(bt);

%Nod = leaves(bt,'dp');

%Nod = tnodes(bt,'dp');

Nod = tnodes(bt);

%size(Nod)

%plot(bt); %cfs=read(bt,'data',Nod(:))

%size(cfs) cfs=[];

dim=size(Nod);

for ii=1:dim(1)

wpc=wpcoef(bt,Nod(ii,:));

%wpc=read(bt,'data',Nod(ii,:));

cfs=[cfs;wpc(:)];

end

x=engsort(cfs);

end function [sortx]=engsort(inx);

sortx=inx.^2;

wp=sort(sortx,'descend');

sortx=cumsum(wp(:));

disp(sortx(end))

sortx=sortx/sortx(end);

%sortx=sortx*(100.0/sortx(end));

end

-----

sig5.txt

0.000000

3.000000

1.247532

-1.082456

-1.489200

-0.642402

-0.102063

0.150076

0.631553

0.821337

0.149639

-0.684489

-0.656090

0.041926

0.422452

0.189428

-0.102536

-0.091313

0.007867

-0.004289

-0.004936

0.075344

0.068230

-0.088631

-0.178296

-0.042943

0.155281

0.175905

0.026200

-0.106516

-0.122575

-0.064517

0.012910

0.085867

0.109416

0.043478

-0.065088

-0.110513

-0.053582

0.036399

0.074659

0.048125

-0.001734

-0.037605

-0.044307

-0.020404

0.018027

0.038989

0.023585

-0.010522

-0.028610

-0.017668

0.005138

0.017576

0.013448

0.000407

-0.010970

-0.012941

-0.004010

0.008402

0.012849

0.005268

-0.006433

-0.011123

-0.005780

0.003353

0.008425

0.006459

-0.000044

-0.005907

-0.006772

-0.002187

0.003805

0.006079

0.003116

-0.001914