EKFfull Class Reference

Extended Kalman Filter in full matrices. More...

#include <libKF.h>

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List of all members.

Public Member Functions

 EKFfull (RV rvx, RV rvy, RV rvu)
 Default constructor.
void set_parameters (diffbifn *pfxu, diffbifn *phxu, const mat Q0, const mat R0)
 Set nonlinear functions for mean values and covariance matrices.
void bayes (const vec &dt)
 Here dt = [yt;ut] of appropriate dimensions.
void set_est (vec mu0, mat P0)
 set estimates
epdf_epdf ()
 dummy!
void bayes (mat Dt)
 Batch Bayes rule (columns of Dt are observations).
const RV_rv () const
 access function
double _ll () const
 access function

Public Attributes

vec mu
 Mean value of the posterior density.
mat P
 Variance of the posterior density.
bool evalll
double ll

Protected Attributes

int dimx
int dimy
int dimu
mat A
mat B
mat C
mat D
mat R
mat Q
mat _Pp
mat _Ry
mat _iRy
mat _K
RV rv
 Random variable of the posterior.
double ll
 Logarithm of marginalized data likelihood.
bool evalll
 If true, the filter will compute likelihood of the data record and store it in ll . Set to false if you want to save time.

Friends

std::ostream & operator<< (std::ostream &os, const KalmanFull &kf)
 print elements of KF


Detailed Description

Extended Kalman Filter in full matrices.

An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.


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

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