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livetrax/libs/qm-dsp/maths/KLDivergence.h
Paul Davis 3deba1921b add queen mary DSP library
git-svn-id: svn://localhost/ardour2/branches/3.0@9029 d708f5d6-7413-0410-9779-e7cbd77b26cf
2011-03-02 12:37:39 +00:00

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1.6 KiB
C++

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