📄 idfig07.m
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% idfig07 -- Ideal Figure 07: Wavelet Shrinkage Damping of Noisy Data
%
% Here we apply the minimax thresholding rule to the
% four noisy signals depicted in Figure 3.
%
% The procedure:
% 1. Transform to Wavelet Domain, Using Nearly Symmetric Wavelet
% with 8 vanishing moments.
% 2. Apply a soft thresholding nonlinearity, with threshold set to
% the magic number \lambda_n
% 3. Transform back to the signal domain.
%
% The reconstructions suppress the noise, while preserving the sharp structure
% in the neighborhood of the highly-variable spatial components.
%
% Compare also the ideal reconstructions of figure 5.
%
global shblocks shbumps shheavi shDoppler
global yblocks ybumps yheavi yDoppler
global L qmf
global t
%
[sbumps,shbumps] = WaveShrink(ybumps ,'MinMax',L,qmf);
[sblocks,shblocks] = WaveShrink(yblocks,'MinMax',L,qmf);
[sheavi,shheavi] = WaveShrink(yheavi ,'MinMax',L,qmf);
[sDoppler,shDoppler] = WaveShrink(yDoppler,'MinMax',L,qmf);
%
%clf;
claxis;
versaplot(221,t,sblocks, [],' 7 (a) WaveSelect[Blocks] ' ,[],[])
versaplot(222,t,sbumps, [],' 7 (b) WaveSelect[Bumps] ' ,[],[])
versaplot(223,t,sheavi, [],' 7 (c) WaveSelect[HeaviSine] ',[],[])
versaplot(224,t,sDoppler,[],' 7 (d) WaveSelect[Doppler] ' ,[],[])
%% 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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