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Recursive direct weight optimization in nonlinear system identification : A minimal probability approach

Author
BAI, Er-Wei1 ; YUN LIU1
[1] Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States
Source

IEEE transactions on automatic control. 2007, Vol 52, Num 7, pp 1218-1231, 14 p ; ref : 24 ref

CODEN
IETAA9
ISSN
0018-9286
Scientific domain
Control theory, operational research
Publisher
Institute of Electrical and Electronics Engineers, New York, NY
Publication country
United States
Document type
Article
Language
English
Author keyword
Direct weight optimization minimum probability nonlinear parameter estimation nonlinear system identification
Keyword (fr)
Approche probabiliste Approximation asymptotique Commande non linéaire Compétitivité Estimation paramètre Identification système Méthode récursive Observateur Optimisation Programmation non linéaire Solution exacte
Keyword (en)
Probabilistic approach Asymptotic approximation Non linear control Competitiveness Parameter estimation System identification Recursive method Observer Optimization Non linear programming Exact solution
Keyword (es)
Enfoque probabilista Aproximación asintótica Control no lineal Competitividad Estimación parámetro Identificación sistema Método recursivo Observador Optimización Programación no lineal Solución exacta
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02D Control theory. Systems / 001D02D05 Modelling and identification

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
18931049

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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