Non Linear Conditional Gaussian. More...

#include <nonlinearanalyticconditionalgaussianodo.h>

Inheritance diagram for BFL::NonLinearAnalyticConditionalGaussianOdo:

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Public Member Functions
virtual MatrixWrapper::Matrix	dfGet (unsigned int i) const

virtual MatrixWrapper::ColumnVector	ExpectedValueGet () const

	NonLinearAnalyticConditionalGaussianOdo (const Gaussian &additiveNoise)
	Constructor. More...

virtual	~NonLinearAnalyticConditionalGaussianOdo ()
	Destructor. More...

Public Member Functions inherited from BFL::AnalyticConditionalGaussianAdditiveNoise
const MatrixWrapper::ColumnVector &	AdditiveNoiseMuGet () const

void	AdditiveNoiseMuSet (const MatrixWrapper::ColumnVector &mu)

const MatrixWrapper::SymmetricMatrix &	AdditiveNoiseSigmaGet () const

void	AdditiveNoiseSigmaSet (const MatrixWrapper::SymmetricMatrix &sigma)

	AnalyticConditionalGaussianAdditiveNoise (const Gaussian &gaus, int num_conditional_arguments=1)

	AnalyticConditionalGaussianAdditiveNoise (int dim=0, int num_conditional_arguments=0)

virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const

virtual	~AnalyticConditionalGaussianAdditiveNoise ()

Public Member Functions inherited from BFL::AnalyticConditionalGaussian
	AnalyticConditionalGaussian (int dim=0, int num_conditional_arguments=0)

virtual	~AnalyticConditionalGaussian ()

Public Member Functions inherited from BFL::ConditionalGaussian
virtual ConditionalGaussian *	Clone () const

	ConditionalGaussian (int dim=0, int num_conditional_arguments=0)

virtual Probability	ProbabilityGet (const MatrixWrapper::ColumnVector &input) const

virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &sample, int method=DEFAULT, void *args=NULL) const

virtual bool	SampleFrom (std::vector< Sample< MatrixWrapper::ColumnVector > > &samples, const int num_samples, int method=DEFAULT, void *args=NULL) const

virtual	~ConditionalGaussian ()

Public Member Functions inherited from ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
const MatrixWrapper::ColumnVector &	ConditionalArgumentGet (unsigned int n_argument) const

virtual void	ConditionalArgumentSet (unsigned int n_argument, const MatrixWrapper::ColumnVector &argument)

const std::vector< MatrixWrapper::ColumnVector > &	ConditionalArgumentsGet () const

virtual void	ConditionalArgumentsSet (std::vector< MatrixWrapper::ColumnVector > ConditionalArguments)

	ConditionalPdf (int dimension=0, unsigned int num_conditional_arguments=0)

unsigned int	NumConditionalArgumentsGet () const

virtual void	NumConditionalArgumentsSet (unsigned int numconditionalarguments)

virtual	~ConditionalPdf ()

Public Member Functions inherited from Pdf< MatrixWrapper::ColumnVector >
unsigned int	DimensionGet () const

virtual void	DimensionSet (unsigned int dim)

	Pdf (unsigned int dimension=0)

virtual bool	SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const

virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const

virtual	~Pdf ()

Private Attributes
MatrixWrapper::Matrix	df

Additional Inherited Members
Protected Attributes inherited from BFL::AnalyticConditionalGaussianAdditiveNoise
MatrixWrapper::ColumnVector	_additiveNoise_Mu

MatrixWrapper::SymmetricMatrix	_additiveNoise_Sigma

Protected Attributes inherited from BFL::ConditionalGaussian
ColumnVector	_diff

Matrix	_Low_triangle

ColumnVector	_Mu

ColumnVector	_samples

ColumnVector	_SampleValue

Detailed Description

Non Linear Conditional Gaussian.

$\mu = Matrix[1] . ConditionalArguments[0] + Matrix[2]. ConditionalArguments[1] + ... + Noise.\mu$
Covariance is independent of the ConditionalArguments, and is the covariance of the Noise pdf

Definition at line 33 of file nonlinearanalyticconditionalgaussianodo.h.

Constructor & Destructor Documentation

◆ NonLinearAnalyticConditionalGaussianOdo()

BFL::NonLinearAnalyticConditionalGaussianOdo::NonLinearAnalyticConditionalGaussianOdo ( const Gaussian & additiveNoise )

Constructor.

Precondition: : Every Matrix should have the same amount of rows! This is currently not checked. The same goes for the number of columns, which should be equal to the number of rows of the corresponding conditional argument!

Parameters

additiveNoise Pdf representing the additive Gaussian uncertainty

Definition at line 27 of file nonlinearanalyticconditionalgaussianodo.cpp.