Brief Applying the EKF to stochastic differential equations with level effects

Authors:
Jan Nygaard Nielsen;Henrik Madsen
Affiliations:
Department of Mathematical Modelling, Technical University of Denmark, Building 321, DK-2800 Lyngby, Denmark;Department of Mathematical Modelling, Technical University of Denmark, Building 321, DK-2800 Lyngby, Denmark
Venue:
Automatica (Journal of IFAC)
Year:
2001

Citing 0
Cited 3

Using a connected filter for structure estimation in perspective systems

WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Brief Sonar-based robot navigation using nonlinear robust observers

Automatica (Journal of IFAC)
Parameter estimation in stochastic grey-box models

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.15

Visualization

Abstract

A transformation is introduced to effectively remove level effects, i.e. the state dependency of the diffusion function, in a restricted class of multivariate stochastic differential equations such that the general continuous-discrete-time nonlinear filtering problem may be solved using new or existing implementations of the extended kalman filter (EKF). An implementation of a quasi-maximum likelihood (QML) method for direct estimation of embedded parameters in nonlinear, multivariate stochastic differential equations using discrete-time input-output data encumbered with additive measurement noise is discussed, and its properties are compared with those provided by another software package.