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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/18141
Title: Nonlinear System Identification by Evolutionary Computation and Recursive Estimation Method
Authors: Jih-Gau Juang 
Bo-Shian Lin
Keywords: nonlinear systems;Evolutionary computation;Recursive estimation;Resonance light scattering;System identification;Convergence;parameter estimation;Mathematical model;Genetic programming;Control system analysis
Issue Date: 8-Jun-2005
Publisher: IEEE
Start page/Pages: 5073-5078
Conference: Proceedings of the 2005, American Control Conference, 2005.
Portland, OR, USA
Abstract: 
Nonlinear system identification using evolutionary computation and recursive estimation method is presented. Four different recursive estimation methods, recursive least-squares, recursive least-squares with exponential forgetting, stochastic algorithm, and projection algorithm, combined with evolution algorithm are used in this study. Conventional system identification using recursive estimation methods are also given for comparison. After test, the proposed scheme has better convergence and accuracy on parameter estimation than the conventional estimation method.
URI: http://scholars.ntou.edu.tw/handle/123456789/18141
ISBN: Print ISBN:0-7803-9098-9
Electronic ISBN:0-7803-9099-7
ISSN: Print ISSN: 0743-1619
Electronic ISSN: 2378-5861
DOI: 10.1109/ACC.2005.1470820
Appears in Collections:通訊與導航工程學系

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