Multi-innovation extended stochastic gradient algorithm for multi-input multi-output controlled autoregressive moving average systems by using the filtering technique

In this paper, we extends the innovation vector to the innovation matrices and presents a filtering based multi-innovation extended stochastic gradient algorithm for multi-input multi-output controlled autoregressive moving average systems. The basic idea is using the filtering technique to transfor...

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Vydané v:	Proceedings of the American Control Conference s. 925 - 929
Hlavní autori:	Jiang, Xiao, Pan, Jian, Wan, Xiangkui, Ding, Feng
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	American Automatic Control Council (AACC) 01.07.2016
Predmet:	Algorithms Autoregressive moving average Autoregressive processes Conferences Control systems Filtering Filtration Innovation Mathematical model MIMO Parameter estimation Signal processing algorithms Stochastic processes Stochasticity Technological innovation
ISSN:	2378-5861
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