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
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18 
19 #ifndef __OPTIMAL_IMPORTANCE_DENSITY__
20 #define __OPTIMAL_IMPORTANCE_DENSITY__
21 
22 #include "analyticconditionalgaussian.h"
23 
24 namespace 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.