Multi-innovation gradient estimation algorithms for multivariate equation-error autoregressive moving average systems based on the filtering technique

This study concentrates on the parameter estimation of multivariate pseudo-linear autoregressive moving average systems by means of the multi-innovation identification theory and data filtering technique. A multi-innovation stochastic gradient algorithm is derived by introducing the innovation lengt...

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Veröffentlicht in:	IET control theory & applications Jg. 13; H. 13; S. 2086 - 2094
Hauptverfasser:	Ma, Ping, Ding, Feng, Hayat, Tasawar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 03.09.2019
Schlagworte:	autoregressive moving average processes data filtering technique filtering theory gradient methods multiinnovation gradient estimation algorithms multiinnovation stochastic gradient algorithm multivariate equation‐error autoregressive multivariate pseudolinear autoregressive moving average systems parameter estimation Research Article multiinnovation gradient estimation algorithms autoregressive moving average processes filtering theory multivariate equation-error autoregressive parameter estimation data filtering technique multivariate pseudolinear autoregressive moving average systems gradient methods multiinnovation stochastic gradient algorithm
ISSN:	1751-8644, 1751-8652
Online-Zugang:	Volltext
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