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Wavelet‐based nonparametric identification technique for nonlinear dynamic systems
Author(s) -
Glabisz Wojciech,
Koźbiał Tomasz,
Napiórkowska Magdalena
Publication year - 2003
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200310436
Subject(s) - wavelet , haar wavelet , identification (biology) , parametric statistics , wavelet packet decomposition , nonparametric statistics , nonlinear system , displacement (psychology) , computer science , signal (programming language) , algorithm , mathematics , wavelet transform , discrete wavelet transform , artificial intelligence , statistics , physics , psychology , botany , quantum mechanics , psychotherapist , biology , programming language
New parametric and non‐parametric identification techniques, based on wavelet expansion, for dynamic systems is shown. The identification results of the parameters of models obtained by the least‐squares method using the Haar wavelet packet analysis of randomly disturbed displacement signal is presented. New differentiation procedure of the measured data exploiting the properties of the wavelet packet analysis of a signal is applied. The non‐parametric identification results of models are known in the form of the restoring force surfaces.