Paul Davis
3deba1921b
git-svn-id: svn://localhost/ardour2/branches/3.0@9029 d708f5d6-7413-0410-9779-e7cbd77b26cf
55 lines
1.6 KiB
C++
55 lines
1.6 KiB
C++
/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
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/*
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QM DSP Library
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Centre for Digital Music, Queen Mary, University of London.
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This file copyright 2008 QMUL.
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License as
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published by the Free Software Foundation; either version 2 of the
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License, or (at your option) any later version. See the file
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COPYING included with this distribution for more information.
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*/
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#ifndef KLDIVERGENCE_H
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#define KLDIVERGENCE_H
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#include <vector>
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using std::vector;
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/**
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* Helper methods for calculating Kullback-Leibler divergences.
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*/
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class KLDivergence
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{
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public:
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KLDivergence() { }
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~KLDivergence() { }
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/**
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* Calculate a symmetrised Kullback-Leibler divergence of Gaussian
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* models based on mean and variance vectors. All input vectors
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* must be of equal size.
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*/
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double distanceGaussian(const vector<double> &means1,
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const vector<double> &variances1,
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const vector<double> &means2,
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const vector<double> &variances2);
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/**
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* Calculate a Kullback-Leibler divergence of two probability
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* distributions. Input vectors must be of equal size. If
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* symmetrised is true, the result will be the symmetrised
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* distance (equal to KL(d1, d2) + KL(d2, d1)).
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*/
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double distanceDistribution(const vector<double> &d1,
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const vector<double> &d2,
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bool symmetrised);
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};
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#endif
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