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Update LTPDAworkbench
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% test_ao_lpsd_variance_montecarlo % % Tests that the standard deviation returned by ao.dy in one % frequency bin is equivalent to the matlab's std taking % considering all realisations % % M Nofrarias 05-08-09 % % $Id: test_ao_lpsd_variance_montecarlo.m,v 1.2 2009/08/11 14:20:10 miquel Exp $ % function test_ao_lpsd_variance_montecarlo() clear % data nsecs = 500; fs = 5; pl = plist('nsecs', nsecs, 'fs', fs, 'tsfcn', 'randn(size(t))'); %lpsd pl2 = plist('Kdes', 20, 'Jdes', 100); % loop for i = 1:100 a(i) = ao(pl); b1(i) = lpsd(a(i),pl2); end %% compare % select a realisation index = 10; % compare estimated std to the one using all realisations clear rel for i =1:len(b1(1)) mn(i) = [mean(b1(:).y(i))]; rel(:,i) = [std(b1(:).y(i))/mn(i) b1(index).dy(i)/b1(index).y(i)]; end % k = find(b1(1).procinfo,'k') figure loglog(b1(1).x,rel') hold loglog(b1(1).x,abs(rel(2,:)-rel(1,:)),'-or') ylabel('difference (%)') % xlabel('Frequency [Hz]') % ylabel('Rel. error') % legend('montecarlo','estimated','difference') % print -deps2c test_ao_lpsd_variance_montecarlo_1.eps % end