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Applying the EKF to stochastic differential equations with level effects

✍ Scribed by Jan Nygaard Nielsen; Henrik Madsen

Publisher: Elsevier Science
Year: 2001
Tongue: English
Weight: 144 KB
Volume: 37
Category: Article
ISSN: 0005-1098
DOI: 10.1016/s0005-1098(00)00128-x

No coin nor oath required. For personal study only.

✦ Synopsis

A transformation is introduced to e!ectively remove level e!ects, i.e. the state dependency of the di!usion function, in a restricted class of multivariate stochastic di!erential equations such that the general continuous}discrete-time nonlinear "ltering problem may be solved using new or existing implementations of the extended kalman "lter (EKF). An implementation of a quasi-maximum likelihood (QML) method for direct estimation of embedded parameters in nonlinear, multivariate stochastic di!erential 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.

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