Title: Parameter estimation for partially observed nonlinear stochastic system

Authors: Chao Wei; Chaobing He

Addresses: School of Mathematics and Statistics, Anyang Normal University, 455000, Anyang, China ' School of Mathematics and Statistics, Anyang Normal University, 455000, Anyang, China

Abstract: This paper is concerned with the parameter estimation problem for partially observed nonlinear stochastic system. The suboptimal estimation of the state is obtained by constructing the extended Kalman filtering equation. The likelihood function is provided based on state estimation equation. The strong consistency of the estimator is proved by applying maximal inequality for martingales, Borel-Cantelli lemma and uniform ergodic theorem. An example is provided to verify the effectiveness of the method.

Keywords: nonlinear stochastic system; state estimation equation; parameter estimation; strong consistency; computing science; mathematics; extended Kalman filtering; suboptimal estimation.

DOI: 10.1504/IJCSM.2019.098739

International Journal of Computing Science and Mathematics, 2019 Vol.10 No.2, pp.150 - 159

Received: 13 Jun 2017
Accepted: 25 Jun 2017
Published online: 02 Apr 2019 *

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