Bayesian Filtering Library Generated from SVN r
optimal_importance_density.h
1// $Id$
2// Copyright (C) 2003 Klaas Gadeyne <first dot last at gmail dot com>
3//
4// This program is free software; you can redistribute it and/or modify
5// it under the terms of the GNU Lesser General Public License as published by
6// the Free Software Foundation; either version 2.1 of the License, or
7// (at your option) any later version.
8//
9// This program is distributed in the hope that it will be useful,
10// but WITHOUT ANY WARRANTY; without even the implied warranty of
11// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12// GNU Lesser General Public License for more details.
13//
14// You should have received a copy of the GNU Lesser General Public License
15// along with this program; if not, write to the Free Software
16// Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
17//
18
19#ifndef __OPTIMAL_IMPORTANCE_DENSITY__
20#define __OPTIMAL_IMPORTANCE_DENSITY__
21
22#include "analyticconditionalgaussian.h"
23
24namespace BFL
25{
27
38 {
39 public:
41
46
47 // Default copy constructor
48
51
52 // redefine pure virtual functions
53 virtual ColumnVector ExpectedValueGet() const;
54 virtual SymmetricMatrix CovarianceGet() const;
55 virtual Matrix dfGet(int i) const;
56
57 private:
58 AnalyticConditionalGaussian * _SystemPdf;
60
61 };
62
63} // End namespace BFL
64
65#include "optimal_importance_density.cpp"
66
67#endif // __OPTIMAL_IMPORTANCE_DENSITY__
Abstract Class representing all FULL Analytical Conditional gaussians.
Optimal importance density for Nonlinear Gaussian SS Models.
OptimalImportanceDensity(AnalyticConditionalGaussian *SystemPdf, LinearAnalyticConditionalGaussian *MeasPdf)
Constructor.
virtual SymmetricMatrix CovarianceGet() const
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
virtual ColumnVector ExpectedValueGet() const
Get the expected value E[x] of the pdf.
virtual ~OptimalImportanceDensity()
Destructor.