# EKFfixed Class Reference

Extended Kalman Filter in full matrices. More...

`#include <ekf_obj.h>`

Inheritance diagram for EKFfixed:

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Collaboration diagram for EKFfixed:

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List of all members.

## Public Member Functions
void | init_ekf (double Tv)
void | ekf (double ux, double uy, double isxd, double isyd)
void | prediction (int *ux)
void | correction (void)
void | update_psi (void)
| EKFfixed (RV rvx, RV rvc)
| Default constructor.
void | bayes (const vec &dt)
| Here dt = [yt;ut] of appropriate dimensions.
epdf & | _epdf ()
| dummy!
void | condition (const vec &Q0)
| Substitute `val` for `rvc`.
void | bayes (mat Dt)
| Batch Bayes rule (columns of Dt are observations).
const RV & | _rv () const
| access function
double | _ll () const
| access function
const RV & | _rvc () const
| access function
## Public Attributes
int | Q [16]
int | R [4]
int | x_est [4]
int | x_pred [4]
int | P_pred [16]
int | P_est [16]
int | Y_mes [2]
int | ukalm [2]
int | Kalm [8]
int | PSI [16]
int | temp15a [16]
int | cA
int | cB
int | cC
int | cG
int | cH
long | temp30a [4]
enorm< fsqmat > | E
mat | Ry
## Protected Attributes
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.
RV | rvc
| Identificator of the conditioning variable.

## 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:

- work/mixpp/pmsm/simulator_zdenek/ekf_example/ekf_obj.h
- work/mixpp/pmsm/simulator_zdenek/ekf_example/ekf_obj.cpp