annotate m-toolbox/classes/+utils/@math/spflat.m @ 44:409a22968d5e default

Add unit tests
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Tue, 06 Dec 2011 18:42:11 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % spflat measures the flatness of a given spectrum
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: spflat measures the flatness of a given spectrum using the
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5 % spectral flatness measure method reported in [1]. It outputs the spectral
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6 % flatness coefficient:
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7 %
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8 % 0 <= sw <= 1
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9 %
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10 % If the spectrum is peaky then sw is near 0. The more the spectrum is flat
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11 % the more sw in near to 1. The sw coefficient is practically calculated by
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12 % the ratio between geometric mean and arithmetic mean of the spectrum.
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13 %
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14 % CALL:
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % sw = spflat(S)
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17 %
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18 % INPUTS:
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19 %
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20 % - S sample power spectrum. More than one sample spectrum can be
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21 % input if they are combined in a single nxm matrix. The algorithm
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22 % calculates sw for each spectrum.
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23 %
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24 % OUTPUT:
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25 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % - sw spectral flatness coefficient. If more than one spectrum
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27 % are input sw is a row vector.
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28 %
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29 % REFERENCES:
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30 %
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31 % [1] S. M. Kay, Modern spectral estimation:Theory and Application,
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32 % Prentice Hall, Englewood Cliffs (1988) ISBN-10: 0130151599. Pages
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33 % ??.
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34 %
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35 %
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36 %
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37 % VERSION: $Id: spflat.m,v 1.2 2009/01/29 08:59:26 luigi Exp $
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38 %
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39 %
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40 % HISTORY: 28-01-2009 L Ferraioli
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 % Creation
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42 %
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43 %
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44 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 function sw = spflat(S)
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46
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47 % willing to work with columns
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48 [a,b] = size(S);
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49 if a>1 && b>1
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50 warning('Matlab:MultipleSpectra','A matrix of data was input; Spectral Flatness Coefficient will be calculated for each column')
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51 else
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52 if a<b
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53 S = S.';
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54 end
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55 end
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56 Ns = size(S,1);
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57 gmean = exp(sum(log(S))./Ns);
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58 sw = gmean./mean(S);
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59
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60 end