Public Member Functions | Private Attributes
BFL::OptimalImportanceDensity Class Reference

Optimal importance density for Nonlinear Gaussian SS Models. More...

#include <optimal_importance_density.h>

Inheritance diagram for BFL::OptimalImportanceDensity:
Inheritance graph

List of all members.

Public Member Functions

virtual SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
virtual Matrix dfGet (int i) const
virtual ColumnVector ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
 OptimalImportanceDensity (AnalyticConditionalGaussian *SystemPdf, LinearAnalyticConditionalGaussian *MeasPdf)
virtual ~OptimalImportanceDensity ()

Private Attributes


Detailed Description

Optimal importance density for Nonlinear Gaussian SS Models.

Describes the optimal importance density for all systems of the form

\[ x_k = f(x_{k-1}) + v_k, \quad v_k \sim N(0, \Sigma_v) \]

\[ z_k = H x_k + w_k, \quad w_k \sim N(0, \Sigma_w) \]

This means all systems with a system equation that uses a AnalyticConditionalGaussian Class and a measurement equation that uses a LinearAnalyticConditionalGaussian class

Definition at line 37 of file optimal_importance_density.h.

Constructor & Destructor Documentation




Member Function Documentation

virtual SymmetricMatrix BFL::OptimalImportanceDensity::CovarianceGet ( ) const [virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
extend this more general to n-th order statistic
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

virtual Matrix BFL::OptimalImportanceDensity::dfGet ( int  i) const [virtual]
virtual ColumnVector BFL::OptimalImportanceDensity::ExpectedValueGet ( ) const [virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Member Data Documentation

Definition at line 59 of file optimal_importance_density.h.

Definition at line 58 of file optimal_importance_density.h.

The documentation for this class was generated from the following file:

Author(s): Klaas Gadeyne, Wim Meeussen, Tinne Delaet and many others. See web page for a full contributor list. ROS package maintained by Wim Meeussen.
autogenerated on Mon Feb 11 2019 03:45:12