DocumentCode
1443836
Title
Some stability properties of dynamic neural networks
Author
Yu, Wen ; Li, XiaoOu
Author_Institution
Dept. de Control Automatico, CINVESTAV-IPN, Mexico City, Mexico
Volume
48
Issue
2
fYear
2001
fDate
2/1/2001 12:00:00 AM
Firstpage
256
Lastpage
259
Abstract
In this paper, the passivity-based approach is used to derive a tuning algorithm for a class of dynamic neural networks. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input-bounded output stability, are guaranteed in certain senses
Keywords
asymptotic stability; neural nets; stability; tuning; asymptotic stability; bounded input-bounded output stability; dynamic neural network; input-to-state stability; passivity; stability properties; tuning algorithm; Asymptotic stability; Circuit stability; Cities and towns; Integrated circuit interconnections; Multilayer perceptrons; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Stability analysis;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/81.904893
Filename
904893
Link To Document