EKFfixed BM BMcond ekf_obj.h int int EKFfixed::Q[16] [16] Q int int EKFfixed::R[4] [4] R int int EKFfixed::x_est[4] [4] x_est int int EKFfixed::x_pred[4] [4] x_pred int int EKFfixed::P_pred[16] [16] P_pred int int EKFfixed::P_est[16] [16] P_est int int EKFfixed::Y_mes[2] [2] Y_mes int int EKFfixed::ukalm[2] [2] ukalm int int EKFfixed::Kalm[8] [8] Kalm int int EKFfixed::PSI[16] [16] PSI int int EKFfixed::temp15a[16] [16] temp15a int int EKFfixed::cA cA int int EKFfixed::cB cB int int EKFfixed::cC cC int int EKFfixed::cG cG int int EKFfixed::cH cH long long EKFfixed::temp30a[4] [4] temp30a enorm< fsqmat > enorm<fsqmat> EKFfixed::E E mat mat EKFfixed::Ry Ry void void EKFfixed::init_ekf (double Tv) init_ekf double Tv void void EKFfixed::ekf (double ux, double uy, double isxd, double isyd) ekf double ux double uy double isxd double isyd void void EKFfixed::prediction (int *ux) prediction int * ux void void EKFfixed::correction (void) correction void void void EKFfixed::update_psi (void) update_psi void EKFfixed::EKFfixed (RV rvx, RV rvc) EKFfixed RV rvx RV rvc Default constructor. void void EKFfixed::bayes (const vec &dt) bayes bayes const vec & dt Here dt = [yt;ut] of appropriate dimensions. BM::evalll BM::ll enorm< sq_T >::set_mu epdf & epdf& EKFfixed::_epdf () _epdf _epdf dummy! void void EKFfixed::condition (const vec &Q0) condition condition const vec & val Substitute val for rvc. void void BM::bayes (mat Dt) bayes mat Dt Batch Bayes rule (columns of Dt are observations). const RV & const RV& BM::_rv () const _rv access function BM::rv double double BM::_ll () const _ll access function BM::ll const RV & const RV& BMcond::_rvc () const _rvc access function BMcond::rvc RV RV BM::rv rv Random variable of the posterior. BM::_rv MPF< BM_T >::MPF EKFfull::set_parameters ARX::structure_est double double BM::ll ll Logarithm of marginalized data likelihood. BM::_ll bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes KalmanCh::bayes EKFfull::bayes ARX::bayes bool bool BM::evalll 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. bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes KalmanCh::bayes EKFfull::bayes ARX::bayes RV RV BMcond::rvc rvc Identificator of the conditioning variable. BMcond::_rvc KFcondR::condition KFcondQR::condition Extended Kalman Filter with full matrices in fixed point arithmetic. An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. BM EKFfixed BMcond enorm< sq_T > R sq_T epdf rv BM rv EKFfixed E fsqmat enorm< fsqmat > R < fsqmat > RV sqmat eEF BMcond rvc EKFfixed_epdf EKFfixed_ll EKFfixed_rv EKFfixed_rvc EKFfixedbayes EKFfixedbayes EKFfixedBM EKFfixedBMcond EKFfixedcA EKFfixedcB EKFfixedcC EKFfixedcG EKFfixedcH EKFfixedcondition EKFfixedcorrection EKFfixedE EKFfixedekf EKFfixedEKFfixed EKFfixedevalll EKFfixedinit_ekf EKFfixedKalm EKFfixedll EKFfixedP_est EKFfixedP_pred EKFfixedprediction EKFfixedPSI EKFfixedQ EKFfixedR EKFfixedrv EKFfixedrvc EKFfixedRy EKFfixedtemp15a EKFfixedtemp30a EKFfixedukalm EKFfixedupdate_psi EKFfixedx_est EKFfixedx_pred EKFfixedY_mes EKFfixed~BM EKFfixed~BMcond