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: */
|
||
|
|
||
|
/*
|
||
|
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
|
||
|
|