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diff --git a/libs/qm-dsp/maths/KLDivergence.h b/libs/qm-dsp/maths/KLDivergence.h
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+/* -*- 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
+