Robust Parametric Identification Procedure for Stochastic Nonlinear Continuous-Discrete Systems

被引：0
|
作者：
Chubich V.M. [1 ]
Kulabukhova S.O. [1 ]
机构：
[1] Novosibirsk State Technical University, Novosibirsk
来源：
Journal of Applied and Industrial Mathematics | 2021年 / 15卷 / 03期
关键词：
anomalous observation; cubature Kalman filter; parametric identification; robust filtering; stochastic nonlinear continuous-discrete system; weighted maximum likelihood estimation;
D O I：
10.1134/S1990478921030030
中图分类号：
学科分类号：
摘要：
Abstract: Basing on the weighted maximum likelihood method and the correntropy cubatureKalman filter, we develop some software for solving the problem of parametric estimation of themodels for the stochastic nonlinear continuous-discrete systems in presence of anomalousobservations in measurement data. The effectiveness of the proposed procedure is demonstratedby two model structures for the stochastic and the grouped nature of anomalous data location. © 2021, Pleiades Publishing, Ltd.
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页码：384 / 392
页数：8
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