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annotate m-toolbox/classes/+utils/@math/freqCorr.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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % FREQCORR Compute correlation between frequency bins
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 % FREQCORR Compute correlation between frequency bins of a spectral
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % estimation given the data window
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5 %
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6 % CALL
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7 %
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8 % Gf = utils.math.freqCorr(w,eta,T)
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9 %
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10 % INPUT
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11 %
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12 % - w, window samples, Nx1 double, N must be the effective length of the
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13 % segments used for spectral estimation. E.g. For a periodogram N is equal
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14 % to the length of the data series. For a WOSA estimation N is the length
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15 % of each averaging segment.
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16 % - eta, frequency lag in Hz, 1x1 double
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17 % - T, sampling time in seconds, 1x1 double
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18 %
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19 % REFERENCES
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20 %
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21 % D. B. Percival and A. T. Walden, Spectral Analysis for Physical
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22 % Applications (Cambridge University Press, Cambridge, 1993) p 231.
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23 %
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24 % L Ferraioli 09-03-2011
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25 %
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26 % $Id: freqCorr.m,v 1.1 2011/03/28 16:37:23 luigi Exp $
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27 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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28 function R = freqCorr(w,eta,T)
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29
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30 Ns = numel(w);
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31 % willing to work with columns
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32 [nn,mm] = size(w);
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33 if nn<mm
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34 w = w.';
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35 end
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36 % make suqre integrable
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37 a = sqrt(sum(w.^2));
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38 w = w./a;
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39
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40 t = 1:Ns;
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41
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42 ww = w.*w;
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43 hh = exp(-1i.*2.*pi.*t.*T.*eta)*ww;
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44 R = abs(hh)^2;
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45
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46
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47 end