MeasurementModel< MeasVar, StateVar > Class Template Reference

#include <measurementmodel.h>

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, const SampleMthd sampling_method=SampleMthd::DEFAULT, void *sampling_args=NULL)
	Simulate the Measurement, given a certain state, and an input.
MeasVar	Simulate (const StateVar &x, const SampleMthd sampling_method=SampleMthd::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??

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.

Constructor & Destructor Documentation

MeasurementModel()

template<typename MeasVar , typename StateVar >

MeasurementModel

(

ConditionalPdf< MeasVar, StateVar > *

Measurementpdf = NULL

)

Constructor.

Parameters

Measurementpdf

ConditionalPdf<MeasVar,StateVar> representing

See also

MEASUREMENT_SIZE, STATE_SIZE, INPUT_SIZE, _MeasurementPdf

Member Function Documentation

MeasurementPdfSet()

template<typename MeasVar , typename StateVar >

void MeasurementPdfSet

(

ConditionalPdf< MeasVar, StateVar > *

pdf

)

Set the MeasurementPDF.

Parameters

pdf	a pointer to the measurement pdf

ProbabilityGet() [1/2]

template<typename MeasVar , typename StateVar >

Probability ProbabilityGet	(	const MeasVar &	z,
		const StateVar &	x
	)

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

ProbabilityGet() [2/2]

template<typename MeasVar , typename StateVar >

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

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

Simulate() [1/2]

template<typename MeasVar , typename StateVar >

MeasVar Simulate	(	const StateVar &	x,
		const SampleMthd	sampling_method = SampleMthd::DEFAULT,
		void *	sampling_args = NULL
	)

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)

Simulate() [2/2]

template<typename MeasVar , typename StateVar >

MeasVar Simulate	(	const StateVar &	x,
		const StateVar &	s,
		const SampleMthd	sampling_method = SampleMthd::DEFAULT,
		void *	sampling_args = NULL
	)

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

Member Data Documentation

_MeasurementPdf

template<typename MeasVar , typename StateVar >

ConditionalPdf<MeasVar,StateVar>* _MeasurementPdf

protected

ConditionalPdf representing .

Definition at line 62 of file measurementmodel.h.

_systemWithoutSensorParams

template<typename MeasVar , typename StateVar >

bool _systemWithoutSensorParams

protected

System with no sensor params??

Definition at line 65 of file measurementmodel.h.

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

• measurementmodel.h