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MeasurementModel< MeasVar, StateVar > Class Template Reference

#include <measurementmodel.h>

Public Member Functions

 MeasurementModel (ConditionalPdf< MeasVar, StateVar > *Measurementpdf=NULL)
 Constructor. More...
 
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. More...
 
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. More...
 
MeasVar Simulate (const StateVar &x, int sampling_method=DEFAULT, void *sampling_args=NULL)
 Simulate the system (no input system) More...
 
Probability ProbabilityGet (const MeasVar &z, const StateVar &x, const StateVar &s)
 Get the probability of a certain measurement. More...
 
Probability ProbabilityGet (const MeasVar &z, const StateVar &x)
 Get the probability of a certain measurement. More...
 

Protected Attributes

ConditionalPdf< MeasVar, StateVar > * _MeasurementPdf
 ConditionalPdf representing $ P(Z_k | X_{k}, U_{k}) $.
 
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 $ P ( Z | X ) $ and $ P ( X_k | X_{k-1} ) $ If $ X_{k-1} $ is discrete, then $ X_{k} $ 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 ( ConditionalPdf< MeasVar, StateVar > *  Measurementpdf = NULL)

Constructor.

Parameters
MeasurementpdfConditionalPdf<MeasVar,StateVar> representing $ P(Z_k | X_{k} (, U_{k})) $
See also
MEASUREMENT_SIZE, STATE_SIZE, INPUT_SIZE, _MeasurementPdf

Definition at line 26 of file measurementmodel.h.

Member Function Documentation

void MeasurementPdfSet ( ConditionalPdf< MeasVar, StateVar > *  pdf)

Set the MeasurementPDF.

Parameters
pdfa pointer to the measurement pdf

Definition at line 95 of file measurementmodel.h.

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
zthe measurement value
xcurrent state of the system
sthe sensor param value
Returns
the "probability" of the measurement

Definition at line 150 of file measurementmodel.h.

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
zthe measurement value
xx current state of the system
Returns
the "probability" of the measurement

Definition at line 161 of file measurementmodel.h.

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.

Parameters
xcurrent state of the system
ssensor parameter
Returns
Measurement generated by simulating the measurement model
Parameters
sampling_methodthe sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
sampling_argsSometimes 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 121 of file measurementmodel.h.

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

Simulate the system (no input system)

Parameters
xcurrent 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_methodthe sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
sampling_argsSometimes a sampling method can have some extra parameters (eg mcmc sampling)

Definition at line 137 of file measurementmodel.h.


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