Identification of a Class of Time-Varying Nonlinear System Based on the Wiener Model with Application to Automotive Engineering

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Identification of a Class of Time-Varying Nonlinear System Based on the Wiener Model with Application to Automotive Engineering

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dc.contributor.author Ralston, J.C.
dc.contributor.author Zoubir, A.M.
dc.contributor.author Boashash, B
dc.date.accessioned 2012-02-15T10:11:52Z
dc.date.available 2012-02-15T10:11:52Z
dc.date.issued 1995-09
dc.identifier.citation IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E78-A No.9 pp.1192-1200 en_US
dc.identifier.issn 0916-8508
dc.identifier.uri http://hdl.handle.net/10576/10786
dc.description This paper presents a time varying nonlinear system identification procedure. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract We consider the identification of a class of systems which are both time-varying and nonlinear. Time-varying nonlinear systems are often encountered in practice, but tend to be avoided due to the difficulties that arise in modelling and estimation. We study a particular time-varying polynomial model, which is a member of the class of time-varying Wiener models. The model can characterise both time-variation and nonlinearity in a straightforward manner, without requiring an excessively large number of coefficients. We formulate a procedure to find least-squares estimates of the model coefficients. An advantage of the approach is that systems with rapidly changing dynamics can be characterised. In addition, we do not require that the input is stationary or Gaussian. The approach is validated with an application to an automobile modelling problem, where a time-varying nonlinear model is seen to more accurately characterise the system than a time-invariant nonlinear one. en_US
dc.language.iso en en_US
dc.publisher IEICE en_US
dc.subject system identification en_US
dc.subject nonlinear en_US
dc.subject time-varying en_US
dc.subject Wiener model en_US
dc.subject automotive engineering en_US
dc.title Identification of a Class of Time-Varying Nonlinear System Based on the Wiener Model with Application to Automotive Engineering
dc.type Article en_US

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