Conditions for attaining the global minimum in maximum likelihood system identification

Y. Zou; W.P. Heath

doi:10.3182/20090706-3-FR-2004.00184

Conditions for attaining the global minimum in maximum likelihood system identification

Y. Zou
, W.P. Heath

University of Manchester

Research output: Contribution to journal › Article › peer-review

Abstract

Maximum likelihood estimation(MLE) is a popular technique in both open and closed loop identification. However when the landscape of likelihood function has several local minima, gradient based optimization might end up with local convergence. To avoid this, various non-local-minimum conditions are derived in this paper. Here we consider different model structures, in particular Output-Error, ARMAX, and Box-Jenkins models

Original language	Unknown
Pages (from-to)	1110-1115
Number of pages	6
Journal	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	42
Issue number	10
Early online date	19 Feb 2010
DOIs	https://doi.org/10.3182/20090706-3-FR-2004.00184
Publication status	Published - 21 Apr 2016
Externally published	Yes

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10.3182/20090706-3-FR-2004.00184

Cite this

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title = "Conditions for attaining the global minimum in maximum likelihood system identification",

abstract = "Maximum likelihood estimation(MLE) is a popular technique in both open and closed loop identification. However when the landscape of likelihood function has several local minima, gradient based optimization might end up with local convergence. To avoid this, various non-local-minimum conditions are derived in this paper. Here we consider different model structures, in particular Output-Error, ARMAX, and Box-Jenkins models",

author = "Y. Zou and W.P. Heath",

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AB - Maximum likelihood estimation(MLE) is a popular technique in both open and closed loop identification. However when the landscape of likelihood function has several local minima, gradient based optimization might end up with local convergence. To avoid this, various non-local-minimum conditions are derived in this paper. Here we consider different model structures, in particular Output-Error, ARMAX, and Box-Jenkins models

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DO - 10.3182/20090706-3-FR-2004.00184

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JO - IFAC Proceedings Volumes (IFAC-PapersOnline)

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