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

#include <conditionalgaussian_additivenoise.h>

Inheritance diagram for BFL::ConditionalGaussianAdditiveNoise:

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:

gaus	Gaussian representing the additive uncertainty
num_conditional_arguments	The number of conditional arguments.

BFL::ConditionalGaussianAdditiveNoise::ConditionalGaussianAdditiveNoise	(	int	dim = `0`,
		int	num_conditional_arguments = `0`
	)

Constructor 2, Gaussian not yet known.

Parameters:

dim	Dimension of state
num_conditional_arguments	The number of conditional arguments.

virtual BFL::ConditionalGaussianAdditiveNoise::~ConditionalGaussianAdditiveNoise ( ) [virtual]

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:

mu	the 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:

sigma the 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:

conditionalgaussian_additivenoise.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation