📄 cspinf08.m
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% cspinf08 -- Closeups of Fully TI Haar Wavelet Shrinkage
%
% Here we test fully translation-invariant denoising, using
% the Stationary Wavelet Transform. This is a method of removing artifacts
% from wavelet thresholding and other de-noising.
% Using this in a clever way, we can average
% the results of de-noising on
% *all* circulant shifts of a signal.
%
% The procedure for DeNoising:
% 1. Translation-Invariant Transform to Wavelet Domain,
% Using Haar Wavelet.
% 2. Apply a Soft thresholding nonlinearity, with threshold set to
% sqrt{2 log(n)}
% 3. Transform back to the signal domain.
%
% We do this on *all* circulant shifts of a signal and
% then average the results.
%
%
% Remark: run CycleSpinInit and cspinf0[12] before this.
% Remark: run cspinf07 before this
% Agenda: %
global yblocks ybumps yheavi yDoppler
global t
global xhblocks xblocks zblocks
%
global xhheavi
%
if isempty(zblocks)
warndlg('Please run figure 6 first and then run this figure');
return;
end
% figure;
ax = [.0 .35 -15 25];
subplot(2,2,1); plot(t,xhblocks,'-'); axis(ax); hold on; plot(t,xblocks,'.')
title(' 8a TI Haar DeNoising & Blocks')
%
subplot(2,2,2);
plot(t,zblocks); axis(ax);
title(' 8b Ordinary Haar DeNoising');
% Revision History
% 09/29/99 MRD declare xblocks etc. global
%% Part of Wavelab Version 850% Built Tue Jan 3 13:20:42 EST 2006% This is Copyrighted Material% For Copying permissions see COPYING.m% Comments? e-mail wavelab@stat.stanford.edu
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