DocumentCode
2667125
Title
Exponential robust stability of stochastic interval Hopfield neural networks with time-varying delays
Author
Xiaolin, Li
Author_Institution
Dept. of Math., Shanghai Univ., Shanghai
fYear
2008
fDate
16-18 July 2008
Firstpage
701
Lastpage
704
Abstract
In this paper, the exponential robust stability for stochastic interval Hopfield neural networks with time-varying delays is investigated. Based on Lyapunov functional approach and linear matrix inequality (LMI) technique, the sufficient conditions are proposed to ensure stochastic interval Hopfield neural networks to be exponential robustly stable.
Keywords
Hopfield neural nets; Lyapunov methods; delays; linear matrix inequalities; robust control; stability; stochastic systems; Lyapunov functional approach; exponential robust stability; linear matrix inequality; stochastic interval Hopfield neural networks; time-varying delays; Artificial neural networks; Biological neural networks; Delay effects; Hopfield neural networks; Linear matrix inequalities; Robust stability; Stability analysis; Stochastic processes; Stochastic systems; Sufficient conditions; Exponential robust stability; Linear matrix inequality (LMI); Lyapunov functional; Stochastic interval hopfield neural networks; Time-varying delays;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location
Kunming
Print_ISBN
978-7-900719-70-6
Electronic_ISBN
978-7-900719-70-6
Type
conf
DOI
10.1109/CHICC.2008.4605578
Filename
4605578
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