Identification of Hammerstein-Wiener models

Title: Identification of Hammerstein-Wiener models
Creator: Wills, Adrian; Schön, Thomas B.; Ljung, Lennart; Ninness, Brett
Relation: Automatica Vol. 49, Issue 1, p. 70-81
Publisher Link: http://dx.doi.org/10.1016/j.automatica.2012.09.018
Publisher: Elsevier Science & Technology
Resource Type: journal article
Date: 2013
Description: This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method developed here addresses the blind Wiener estimation problem as a special case.
Subject: system identification; Hammerstein; maximum likelihood; Wiener; block-oriented models; nonlinear models; dynamic systems; Monte Carlo method; smoothing; expectation maximization algorithm; particle methods
Identifier: http://hdl.handle.net/1959.13/1295163
Identifier: uon:18962
Identifier: ISSN:0005-1098
Language: eng
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