📄 adfig14.m
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% adfig14 -- Adapt Figure 14: AutoTrunc: Fourier Truncated
% Reconstructions from Noisy Data;
%
% Here we depict a reconstruction using truncated Fourier expansions,
% in which only the low-order fourier components of the noisy signal
% are retained in reconstruction. The cut-off point for reconstruction
% in the frequency domain is automatically chosen; it is the empirical
% minimizer of the Stein Unbiased Estimate of Risk among truncation rules.
%
global yblocks ybumps yheavi yDoppler
global t
%
%clf;
xhat = AutoTrunc(yblocks,1.);
versaplot(221,t,xhat,[],' 14 (a) AutoTrunc[Blocks]',[],[])
%
xhat = AutoTrunc(ybumps,1.);
versaplot(222,t,xhat,[],' 14 (b) AutoTrunc[Bumps]',[],[])
%
xhat = AutoTrunc(yheavi,1.);
versaplot(223,t,xhat,[],' 14 (c) AutoTrunc[HeaviSine]',[],[])
%
xhat = AutoTrunc(yDoppler,1.);
versaplot(224,t,xhat,[],' 14 (d) AutoTrunc[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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