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Identification of time‐delay Markov jump autoregressive exogenous systems with expectation‐maximization algorithm
Author(s) -
Chen Xin,
Zhao Shunyi,
Liu Fei
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2807
Subject(s) - autoregressive model , identification (biology) , markov chain , jump , expectation–maximization algorithm , maximization , computer science , hidden markov model , algorithm , markov model , mathematical optimization , mathematics , maximum likelihood , artificial intelligence , machine learning , econometrics , statistics , botany , physics , quantum mechanics , biology
Summary This paper is concerned with the identification problem of the Markov jump autoregressive exogenous system with an unknown time delay. The considered problem is solved using the expectation‐maximization algorithm, which estimates the parameters of local models, Markov transition probabilities, and time delay simultaneously. A numerical example and a simulated continuous fermentation reactor example are given to illustrate the capability of the proposed method. It shows that the influences of time delay during identification can be overcome by the proposed algorithm effectively.