Data filtering-based recursive identification for an exponential autoregressive moving average model by using the multi-innovation theory

This study employs the data filtering technique to investigate the recursive identification problems for a non-linear exponential autoregressive model with moving average noise, i.e. the ExpARMA model. Whitening the ExpARMA model by a linear filter, the original identification model is divided into...

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Veröffentlicht in:	IET control theory & applications Jg. 14; H. 17; S. 2526 - 2534
Hauptverfasser:	Xu, Huan, Ma, Fengying, Ding, Feng, Xu, Ling, Alsaedi, Ahmed, Hayat, Tasawar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 26.11.2020
Schlagworte:	autoregressive processes average noise coloured noise model data filtering‐based recursive identification ExpARMA model filtering theory filtering‐based multiinnovation extended stochastic gradient algorithm gradient methods linear filter multiinnovation identification theory nonlinear exponential autoregressive model recursive estimation Research Article nonlinear exponential autoregressive model linear filter filtering theory average noise recursive estimation coloured noise model autoregressive processes data filtering-based recursive identification filtering-based multiinnovation extended stochastic gradient algorithm gradient methods multiinnovation identification theory ExpARMA model
ISSN:	1751-8644, 1751-8652
Online-Zugang:	Volltext
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