Some new results on system identification with dynamic neural networks

Authors
Citation
W. Yu et Xo. Li, Some new results on system identification with dynamic neural networks, IEEE NEURAL, 12(2), 2001, pp. 412-417
Citations number
17
Language
INGLESE
art.tipo
Article
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON NEURAL NETWORKS
ISSN journal
1045-9227 → ACNP
Volume
12
Issue
2
Year of publication
2001
Pages
412 - 417
Database
ISI
SICI code
1045-9227(200103)12:2<412:SNROSI>2.0.ZU;2-S
Abstract
Nonlinear system on-line identification via dynamic neural networks is stud ied in this paper. The main contribution of the paper is that the passivity approach is applied to access several new stable properties of neuro ident ification. The conditions for passivity, stability, asymptotic stability, a nd input-to-state stability are established in certain senses. We conclude that the gradient descent algorithm for weight adjustment is stable in an L -infinity sense and robust to any bounded uncertainties.