Public Member Functions | Protected Attributes
BFL::ConditionalGaussianAdditiveNoise Class Reference

Abstract Class representing all Conditional Gaussians with additive gaussian noise. More...

#include <conditionalgaussian_additivenoise.h>

Inheritance diagram for BFL::ConditionalGaussianAdditiveNoise:
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List of all members.

Public Member Functions

const MatrixWrapper::ColumnVector & AdditiveNoiseMuGet () const
 Get the mean Value of the Additive Gaussian uncertainty.
void AdditiveNoiseMuSet (const MatrixWrapper::ColumnVector &mu)
 Set the mean Value of the Additive Gaussian uncertainty.
const
MatrixWrapper::SymmetricMatrix & 
AdditiveNoiseSigmaGet () const
 Get the covariance matrix of the Additive Gaussian uncertainty.
void AdditiveNoiseSigmaSet (const MatrixWrapper::SymmetricMatrix &sigma)
 Set the covariance of the Additive Gaussian uncertainty.
 ConditionalGaussianAdditiveNoise (const Gaussian &gaus, int num_conditional_arguments=1)
 Constructor.
 ConditionalGaussianAdditiveNoise (int dim=0, int num_conditional_arguments=0)
 Constructor 2, Gaussian not yet known.
virtual
MatrixWrapper::SymmetricMatrix 
CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
virtual ~ConditionalGaussianAdditiveNoise ()
 Destructor.

Protected Attributes

MatrixWrapper::ColumnVector _additiveNoise_Mu
 additive noise expected value
MatrixWrapper::SymmetricMatrix _additiveNoise_Sigma
 additive noise covariance

Detailed Description

Abstract Class representing all Conditional Gaussians with additive gaussian noise.

This class represents all Pdf's of the type

\[ P ( A | B, C, D, ... ) \]

where

\[ \mu_A = f(B,C,D, ...) + mu_{additiveNoise} \]

and

\[ \Sigma_A = \Sigma_{additiveNoise} \]

and

\[ A = N(\mu_A, \Sigma_A) \]

f is not necessarily a analytical function

Definition at line 39 of file conditionalgaussian_additivenoise.h.


Constructor & Destructor Documentation

BFL::ConditionalGaussianAdditiveNoise::ConditionalGaussianAdditiveNoise ( const Gaussian gaus,
int  num_conditional_arguments = 1 
)

Constructor.

Parameters:
gausGaussian representing the additive uncertainty
num_conditional_argumentsThe number of conditional arguments.
BFL::ConditionalGaussianAdditiveNoise::ConditionalGaussianAdditiveNoise ( int  dim = 0,
int  num_conditional_arguments = 0 
)

Constructor 2, Gaussian not yet known.

Parameters:
dimDimension of state
num_conditional_argumentsThe number of conditional arguments.

Destructor.


Member Function Documentation

const MatrixWrapper::ColumnVector& BFL::ConditionalGaussianAdditiveNoise::AdditiveNoiseMuGet ( ) const

Get the mean Value of the Additive Gaussian uncertainty.

Returns:
the mean Value of the Additive Gaussian uncertainty
void BFL::ConditionalGaussianAdditiveNoise::AdditiveNoiseMuSet ( const MatrixWrapper::ColumnVector &  mu)

Set the mean Value of the Additive Gaussian uncertainty.

Parameters:
muthe mean Value of the Additive Gaussian uncertainty
const MatrixWrapper::SymmetricMatrix& BFL::ConditionalGaussianAdditiveNoise::AdditiveNoiseSigmaGet ( ) const

Get the covariance matrix of the Additive Gaussian uncertainty.

Returns:
the mean Value of the Additive Gaussian uncertainty
void BFL::ConditionalGaussianAdditiveNoise::AdditiveNoiseSigmaSet ( const MatrixWrapper::SymmetricMatrix &  sigma)

Set the covariance of the Additive Gaussian uncertainty.

Parameters:
sigmathe covariance matrix of the Additive Gaussian uncertainty
virtual MatrixWrapper::SymmetricMatrix BFL::ConditionalGaussianAdditiveNoise::CovarianceGet ( ) const [virtual]

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

Get first order statistic (Covariance) of this AnalyticPdf

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

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


Member Data Documentation

MatrixWrapper::ColumnVector BFL::ConditionalGaussianAdditiveNoise::_additiveNoise_Mu [protected]

additive noise expected value

Definition at line 94 of file conditionalgaussian_additivenoise.h.

MatrixWrapper::SymmetricMatrix BFL::ConditionalGaussianAdditiveNoise::_additiveNoise_Sigma [protected]

additive noise covariance

Definition at line 97 of file conditionalgaussian_additivenoise.h.


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


bfl
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 Fri Aug 28 2015 10:10:22