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;