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annotate m-toolbox/test/test_ao_cpsd_variance_montecarlo.m @ 19:69e3d49b4b0c database-connection-manager

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Update ltpda_uo.fromRepository
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % test_ao_cpsd_variance_montecarlo
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2 %
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3 % Tests that the standard deviation returned by ao.dy in one
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4 % frequency bin is equivalent to the matlab's std taking
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5 % considering all realisations
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6 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % M Nofrarias 22-07-09
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8 %
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9 % $Id: test_ao_cpsd_variance_montecarlo.m,v 1.1 2009/08/11 14:20:11 miquel Exp $
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10
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11
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12
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13 clear
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14
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15 % data
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16 nsecs = 200;
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17 fs = 10;
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18 pl = plist('nsecs', nsecs, 'fs', fs, 'tsfcn', 'randn(size(t))');
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19
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20
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % Make a filter
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22 f1 = miir(plist('type', 'highpass', 'fc', 4, 'fs', fs));
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23
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24 % loop
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25 for i = 1:100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 a1 = ao(pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 a2 = filter(a1,plist('filter', f1));
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28 b(i) = cpsd(a1,a2,plist('Nfft',100,'order',-1));
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29 end
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30
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31 %% mean
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32
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33 clear rel
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34 for i =1:len(b(1))
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35 mn(i) = [mean(b(:).y(i))]; % both means are equal
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36 rel(:,i) = [std(b(:).y(i)) mean(b(:).dy(i))]/abs(mn(i));
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37 end
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38
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39 figure
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40 loglog(b(1).x,rel')
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41 figure
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42 loglog(b(1).x(:),abs(rel(2,:)-rel(1,:)))
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