📄 corfig01.m
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% corfig01 - Correl Figure 01: Simulated Series exhibiting long range
% correlation
%
% 2048 points are simulated from a mean-zero long-range dependent
% Gaussian process with spectral density approximately proportional to
% (frequency)^{-0.9}.
%
% (a) Part of the series,
%
% (b) Estimated spectral density of the data shown in (a),
%
% (c) Discrete wavelet transform of the series using Daubechies' nearly
% symmetric wavelet of order 8. The coefficients are shown scaled
% relative to the largest coefficient at all levels.
%
% (d) Sample standard deviations (plotted on a logarithmic scale)
% of the various levels of the discrete wavelet transform shown in (c).
global N
global t
global L qmf alpha
global zz
%clf;
[n,J] = dyadlength(zz);
%versaplot(221, (1:n)./n, zz,[],'(a) Sample Path of FRAC noise', [0 1 -5 5],[])
versaplot(221, (1:n)./n, zz,[],'(a)', [0 1 -5 5],[])
xlabel('time')
subplot(222)
[pzz, fzz] = spectrum( zz );
semilogy( 1024.*fzz, pzz(:,1))
axis([0 1024 .01 10]);
title( '(b)')
%title( '(b) Spectral density ')
xlabel('frequency')
ylabel('spectral density')
subplot(223)
wc = FWT_PO(zz,2,qmf);
PlotWaveCoeffLocal(wc, 4, 0);
title( '(c)')
%title( '(c) Near Symm 8 Wavelet Coefficients')
xlabel('time')
ylabel('resolution level')
subplot(224)
stds = ScaleMaker( wc, 2, 'std');
indvec = 2:(J-1);
semilogy( indvec , stds(indvec),'*' );
axis( [0 12 .25 4 ]);
set( gca, 'YTick', [.5 1 2 4] );
title('(d)')
%title('(d) SDs of Wave Coeffs by level')
xlabel('resolution level')
ylabel('std. deviation')
%% 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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