www.gusucode.com > wavelet 源码程序 matlab案例代码 > wavelet/ComplexDualTreeWaveletTransformExample.m

    %% Complex Dual-Tree Wavelet Transform  
% Obtain the complex dual-tree wavelet transform of the noisy Doppler signal.
% The FIR filters in the first and subsequent stages result in an approximately
% analytic wavelet as required.   

%% 
% Create the first-stage analysis filters for the two trees. 
  Faf{1} = [0         0
   -0.0884   -0.0112
    0.0884    0.0112
    0.6959    0.0884
    0.6959    0.0884
    0.0884   -0.6959
   -0.0884    0.6959
    0.0112   -0.0884
    0.0112   -0.0884
         0         0];
Faf{2} = [ 0.0112  0
    0.0112         0
   -0.0884   -0.0884
    0.0884   -0.0884
    0.6959    0.6959
    0.6959   -0.6959
    0.0884    0.0884
   -0.0884    0.0884
         0    0.0112
         0   -0.0112];  

%% 
% Create the analysis filters for subsequent stages of the multiresolution
% analysis. 
af{1} = [ 0.0352         0
         0         0
   -0.0883   -0.1143
    0.2339         0
    0.7603    0.5875
    0.5875   -0.7603
         0    0.2339
   -0.1143    0.0883
         0         0
         0   -0.0352];

af{2} = [0   -0.0352
         0         0
   -0.1143    0.0883
         0    0.2339
    0.5875   -0.7603
    0.7603    0.5875
    0.2339         0
   -0.0883   -0.1143
         0         0
    0.0352         0];  

%% 
% Load the noisy Doppler signal and obtain the complex dual-tree wavelet
% transform down to level 4. 
load noisdopp;
wt = dddtree('cplxdt',noisdopp,4,Faf,af);  

%% 
% Plot an approximation based on the level-four approximation coefficients. 
xapp = dddtreecfs('r',wt,'scale',{5});
plot(noisdopp);  hold on;
plot(cell2mat(xapp),'r','linewidth',3);
axis tight;