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Wiener–haar expansion for the modeling and prediction of the dynamic behavior of self-excited nonlinear uncertain systems / Lyes Nechak in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 134 N° 5 (Septembre 2012) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 134 N° 5 (Septembre 2012) . - 11 p. Titre : Wiener–haar expansion for the modeling and prediction of the dynamic behavior of self-excited nonlinear uncertain systems Type de document : texte imprimé Auteurs : Lyes Nechak, Auteur ; Sébastien Berger, Auteur ; Evelyne Aubry, Auteur Année de publication : 2012 Article en page(s) : 11 p. Note générale : Dynamic systems Langues : Anglais (eng) Mots-clés : Uncertain  nonlinear  systems  Self-excited  systems  Modeling  Prediction  Generalized  polynominal  chaos  Wiener-haar  chaos  Mallat  algorithm  Nonintrusive  approaches Index. décimale : 629.8 Résumé : This paper deals with the modeling and the prediction of the dynamic behavior of uncertain nonlinear systems. An efficient method is proposed to treat these problems. It is based on the Wiener–Haar chaos concept resulting from the polynomial chaos theory and it generalizes the use of the multiresolution analysis well known in the signal processing theory. The method provides a powerful tool to describe stochastic processes as series of orthonormal piecewise functions whose weighting coefficients are identified using the Mallat pyramidal algorithm. This paper shows that the Wiener–Haar model allows an efficient description and prediction of the dynamic behavior of nonlinear systems with probabilistic uncertainty in parameters. Its contribution, compared to the representation using the generalized polynomial chaos model, is illustrated by evaluating the two models via their application to the problems of the modeling and the prediction of the dynamic behavior of a self-excited uncertain nonlinear system. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000134000005 [...] [article] Wiener–haar expansion for the modeling and prediction of the dynamic behavior of self-excited nonlinear uncertain systems [texte imprimé] / Lyes Nechak, Auteur ; Sébastien Berger, Auteur ; Evelyne Aubry, Auteur . - 2012 . - 11 p. Dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 134 N° 5 (Septembre 2012) . - 11 p. Mots-clés : Uncertain  nonlinear  systems  Self-excited  systems  Modeling  Prediction  Generalized  polynominal  chaos  Wiener-haar  chaos  Mallat  algorithm  Nonintrusive  approaches Index. décimale : 629.8 Résumé : This paper deals with the modeling and the prediction of the dynamic behavior of uncertain nonlinear systems. An efficient method is proposed to treat these problems. It is based on the Wiener–Haar chaos concept resulting from the polynomial chaos theory and it generalizes the use of the multiresolution analysis well known in the signal processing theory. The method provides a powerful tool to describe stochastic processes as series of orthonormal piecewise functions whose weighting coefficients are identified using the Mallat pyramidal algorithm. This paper shows that the Wiener–Haar model allows an efficient description and prediction of the dynamic behavior of nonlinear systems with probabilistic uncertainty in parameters. Its contribution, compared to the representation using the generalized polynomial chaos model, is illustrated by evaluating the two models via their application to the problems of the modeling and the prediction of the dynamic behavior of a self-excited uncertain nonlinear system. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000134000005 [...]