📄 idfig04.m
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% idfig04 -- Ideal Figure 04: S8 Wavelet Coefficients of Four Noisy datasets
%
% Here we display the wavelet coefficients of the noisy datasets,
% stratified by scale and location. The noise in these empirical
% wavelet coefficients is a white noise and hence about the same
% in every coefficient.
%
% The signal pokes up above the noise only in locations of
% significant spatial variability.
%
global yblocks ybumps yheavi yDoppler
global wblocks wbumps wheavi wDoppler
global L qmf
%
%clf;
claxis
%
subplot(221)
wblocks = FWT_PO(yblocks,L,qmf);
IMJPlotWaveCoeff(wblocks,L,0.05);
title(' 4 (a) WT[Noisy Blocks] ')
%
subplot(222)
wbumps = FWT_PO(ybumps,L,qmf);
IMJPlotWaveCoeff(wbumps,L,0.05);
title(' 4 (b) WT[Noisy Bumps] ')
%
subplot(223)
wheavi = FWT_PO(yheavi,L,qmf);
IMJPlotWaveCoeff(wheavi,L,0.05);
title(' 4 (c) WT[Noisy HeaviSine] ')
%
subplot(224)
wDoppler = FWT_PO(yDoppler,L,qmf);
IMJPlotWaveCoeff(wDoppler,L,0.05);
title(' 4 (d) WT[Noisy Doppler] ')
% need to hand scale plots so noise is more equalized!
%% Part of Wavelab Version 850% Built Tue Jan 3 13:20:41 EST 2006% This is Copyrighted Material% For Copying permissions see COPYING.m% Comments? e-mail wavelab@stat.stanford.edu
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