Recursive optimization of state estimation of dynamic processes in the presence of patchy outliers in observations

Recursive optimization of state estimation of dynamic processes in the presence of patchy outliers in observations

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Article ID: iaor20012095
Country: Lithuania
Volume: 10
Issue: 3
Start Page Number: 297
End Page Number: 312
Publication Date: Jul 1999
Journal: Informatica
Authors:
Keywords: Kalman filter
Abstract:

In an earlier paper, the problem of recursive estimation of the state of linear dynamic systems, described by an autoregressive model (AR), in the presence of time-varying outliers in observations to be processed has been considered. An approach to the robust recursive state estimation has been obtained and proved by estimating the real chemical process. The aim of the given paper is the development of the above mentioned approach for the robust recursive state estimation of an autoregressive-moving average (ARMA) process in a case of additive noises with patchy outliers. The results of numerical simulation and the state estimation of the AR model and the real chemical process, described by the ARMA model, which is chosen from the same book of Box and Jenkins, are given.

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