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Structure identification of a class of non-linear systems using correlation and bispectrum approaches

Emara-Shabaik, H.E. and Moustafa, K.A.F. and Talaq, J.H.S. (1996) Structure identification of a class of non-linear systems using correlation and bispectrum approaches. Control '96, UKACC International conference (Conf. Publ. No. 427), 1.

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Abstract

The class of nonlinear systems studied in this paper is assumed to be modeled by block-cascades. Such cascades are composed of a dynamic linear block (L) in cascade with a zero-memory nonlinear block (N) followed by another dynamic linear block (L). This class of models is extensively used to represent nonlinear dynamic systems and is known in the literature as Wiener-Hammerstein models. Using a zero-mean stationary white Gaussian process as an input to such models, a structure identification criterion is developed based on the bispectrum and bicoherence of the output sequence only. A comparison between the developed criterion and other cross-correlation based criterion is given.



Item Type:Article
Date:September 1996
Date Type:Publication
Subjects:Computer
Divisions:College Of Computer Sciences and Engineering > Systems Engineering Dept
Creators:Emara-Shabaik, H.E. and Moustafa, K.A.F. and Talaq, J.H.S.
ID Code:14160
Deposited By:KFUPM ePrints Admin
Deposited On:24 Jun 2008 16:24
Last Modified:12 Apr 2011 13:15

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