Public Member Functions
BFL::NonLinearAnalyticConditionalGaussianMobile Class Reference

Non Linear Conditional Gaussian. More...

#include <nonlinearanalyticconditionalgaussianmobile.h>

Inheritance diagram for BFL::NonLinearAnalyticConditionalGaussianMobile:
Inheritance graph
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List of all members.

Public Member Functions

virtual MatrixWrapper::Matrix dfGet (unsigned int i) const
 returns derivative from function to n-th conditional variable
virtual MatrixWrapper::Matrix dfGet (unsigned int i) const
 returns derivative from function to n-th conditional variable
virtual MatrixWrapper::ColumnVector ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
virtual MatrixWrapper::ColumnVector ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
 NonLinearAnalyticConditionalGaussianMobile (const Gaussian &additiveNoise)
 Constructor.
 NonLinearAnalyticConditionalGaussianMobile (const Gaussian &additiveNoise)
 Constructor.
virtual ~NonLinearAnalyticConditionalGaussianMobile ()
 Destructor.
virtual ~NonLinearAnalyticConditionalGaussianMobile ()
 Destructor.

Detailed Description

Non Linear Conditional Gaussian.

Definition at line 34 of file compare_filters/nonlinearanalyticconditionalgaussianmobile.h.


Constructor & Destructor Documentation

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:
ratio,:vector containing the different matrices of the linear relationship between the conditional arguments and $\mu$
additiveNoisePdf representing the additive Gaussian uncertainty

Definition at line 29 of file compare_filters/nonlinearanalyticconditionalgaussianmobile.cpp.

Destructor.

Definition at line 35 of file compare_filters/nonlinearanalyticconditionalgaussianmobile.cpp.

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:
ratio,:vector containing the different matrices of the linear relationship between the conditional arguments and $\mu$
additiveNoisePdf representing the additive Gaussian uncertainty

Destructor.


Member Function Documentation

virtual MatrixWrapper::Matrix BFL::NonLinearAnalyticConditionalGaussianMobile::dfGet ( unsigned int  i) const [virtual]

returns derivative from function to n-th conditional variable

Parameters:
iNumber of the conditional variable to use for partial derivation
Returns:
Partial derivative with respect to conditional variable i

Reimplemented from BFL::AnalyticConditionalGaussian.

Matrix BFL::NonLinearAnalyticConditionalGaussianMobile::dfGet ( unsigned int  i) const [virtual]

returns derivative from function to n-th conditional variable

Parameters:
iNumber of the conditional variable to use for partial derivation
Returns:
Partial derivative with respect to conditional variable i

Reimplemented from BFL::AnalyticConditionalGaussian.

Definition at line 47 of file compare_filters/nonlinearanalyticconditionalgaussianmobile.cpp.

virtual MatrixWrapper::ColumnVector BFL::NonLinearAnalyticConditionalGaussianMobile::ExpectedValueGet ( ) const [virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 37 of file compare_filters/nonlinearanalyticconditionalgaussianmobile.cpp.


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


bfl
Author(s): Klaas Gadeyne, Wim Meeussen, Tinne Delaet and many others. See web page for a full contributor list. ROS package maintained by Wim Meeussen.
autogenerated on Sun Oct 5 2014 22:29:53