MeasurementModel< MeasVar, StateVar > Class Template Reference

#include <measurementmodel.h>

List of all members.

Public Member Functions
	MeasurementModel (ConditionalPdf< MeasVar, StateVar > *Measurementpdf=NULL)
	Constructor.
virtual	~MeasurementModel ()
	Destructor.
int	MeasurementSizeGet () const
	Get Measurement Size.
bool	SystemWithoutSensorParams () const
	Number of Conditional Arguments.
ConditionalPdf< MeasVar, StateVar > *	MeasurementPdfGet ()
	Get the MeasurementPDF.
void	MeasurementPdfSet (ConditionalPdf< MeasVar, StateVar > *pdf)
	Set the MeasurementPDF.
MeasVar	Simulate (const StateVar &x, const StateVar &s, int sampling_method=DEFAULT, void *sampling_args=NULL)
	Simulate the Measurement, given a certain state, and an input.
MeasVar	Simulate (const StateVar &x, int sampling_method=DEFAULT, void *sampling_args=NULL)
	Simulate the system (no input system).
Probability	ProbabilityGet (const MeasVar &z, const StateVar &x, const StateVar &s)
	Get the probability of a certain measurement.
Probability	ProbabilityGet (const MeasVar &z, const StateVar &x)
	Get the probability of a certain measurement.
Protected Attributes
ConditionalPdf< MeasVar, StateVar > *	_MeasurementPdf
	ConditionalPdf representing .
bool	_systemWithoutSensorParams
	System with no sensor params??

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Detailed Description

template<typename MeasVar, typename StateVar>
class BFL::MeasurementModel< MeasVar, StateVar >

Template class representing all possible (continu and discrete) Measurement Models

Todo:

Check if there should be a "model" base class...

Note:

Contrary to the system model, this template class has 2 template arguments: this is because of the different nature of the 2 conditional densities and If is discrete, then will also be discrete, but a discrete state doesn't automatically imply a discrete measurement (as is proven in ASR!)

Definition at line 53 of file measurementmodel.h.

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Constructor & Destructor Documentation

MeasurementModel

(

ConditionalPdf< MeasVar, StateVar > *

Measurementpdf = NULL

)

[inline]

Constructor.

Parameters:

Measurementpdf

ConditionalPdf<MeasVar,StateVar> representing

See also:

MEASUREMENT_SIZE, STATE_SIZE, INPUT_SIZE, _MeasurementPdf

Definition at line 162 of file measurementmodel.h.

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Member Function Documentation

void MeasurementPdfSet

(

ConditionalPdf< MeasVar, StateVar > *

pdf

)

[inline]

Set the MeasurementPDF.

Parameters:

pdf

a pointer to the measurement pdf

Definition at line 231 of file measurementmodel.h.

Probability ProbabilityGet	(	const MeasVar &	z,
		const StateVar &	x
	)			[inline]

Get the probability of a certain measurement.

(measurement independent of input) gived a certain state and input

Parameters:

	z	the measurement value
	x	x current state of the system

Returns:

the "probability" of the measurement

Definition at line 297 of file measurementmodel.h.

Probability ProbabilityGet	(	const MeasVar &	z,
		const StateVar &	x,
		const StateVar &	s
	)			[inline]

Get the probability of a certain measurement.

given a certain state and input

Parameters:

	z	the measurement value
	x	current state of the system
	s	the sensor param value

Returns:

the "probability" of the measurement

Definition at line 286 of file measurementmodel.h.

MeasVar Simulate	(	const StateVar &	x,
		int	sampling_method = DEFAULT,
		void *	sampling_args = NULL
	)			[inline]

Simulate the system (no input system).

Parameters:

x

current state of the system

Returns:

State where we arrive by simulating the measurement model

Note:

Maybe the return value would better be a Sample<StateVar> instead of a StateVar

Parameters:

	sampling_method	the sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
	sampling_args	Sometimes a sampling method can have some extra parameters (eg mcmc sampling)

Definition at line 273 of file measurementmodel.h.

MeasVar Simulate	(	const StateVar &	x,
		const StateVar &	s,
		int	sampling_method = DEFAULT,
		void *	sampling_args = NULL
	)			[inline]

Simulate the Measurement, given a certain state, and an input.

Parameters:

	x	current state of the system
	s	sensor parameter

Returns:

Measurement generated by simulating the measurement model

Parameters:

	sampling_method	the sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
	sampling_args	Sometimes a sampling method can have some extra parameters (eg mcmc sampling)

Note:

Maybe the return value would better be a Sample<StateVar> instead of a StateVar

Definition at line 257 of file measurementmodel.h.

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

• measurementmodel.h