QVision: Qt's Image, Video and Computer Vision Library

00001 /*
00002  *      Copyright (C) 2007, 2008, 2009, 2010, 2011, 2012. PARP Research Group.
00003  *      <http://perception.inf.um.es>
00004  *      University of Murcia, Spain.
00005  *
00006  *      This file is part of the QVision library.
00007  *
00008  *      QVision is free software: you can redistribute it and/or modify
00009  *      it under the terms of the GNU Lesser General Public License as
00010  *      published by the Free Software Foundation, version 3 of the License.
00011  *
00012  *      QVision is distributed in the hope that it will be useful,
00013  *      but WITHOUT ANY WARRANTY; without even the implied warranty of
00014  *      MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
00015  *      GNU Lesser General Public License for more details.
00016  *
00017  *      You should have received a copy of the GNU Lesser General Public
00018  *      License along with QVision. If not, see <http://www.gnu.org/licenses/>.
00019  */
00020 
00024 
00025 #include <qvmath/qvstatistics.h>
00026 
00027 #ifdef QVMATRIXALGEBRA_AVAILABLE
00028 double BhattacharyyaDistance(const QVVector &m1, const QVMatrix &S1, const QVVector &m2, const QVMatrix &S2)
00029     {
00030     QVVector diff = m2-m1;
00031     QVMatrix mS = (S1+S2)/2;
00032     QVMatrix inv = mS.inverse();
00033     double value = (diff*(inv*diff))/8 + log(mS.det()/sqrt(S1.det()*S2.det()))/2;
00034     return value;
00035     }
00036 
00037 QVVector qvLinearRegularizedRegression(const QVMatrix &A, const QVVector &b, const QVMatrix &Gamma)
00038     {
00039     const QVMatrix tikhonovMatrix = (Gamma == QVMatrix())? QVMatrix::identity(A.getCols()): Gamma;
00040     return pseudoInverse(A.transpose()*A + tikhonovMatrix)*A.transpose() * b;
00041     }
00042 #endif
00043 
00044 double randomNormalValue(const double mean, const double variance)
00045     {
00046         const double    U = double( rand() % (RAND_MAX) ) / double(RAND_MAX),
00047                                 V = double( rand() % (RAND_MAX) ) / double(RAND_MAX);
00048 
00049     const double X = sqrt(-2*log(U))*sin(2*PI*V);
00050 
00051     return X * sqrt(variance) + mean;
00052     }
src/qvmath/qvstatistics.cpp
