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Delay-dependent exponential stability for uncertain stochastic Hopfield neural networks with time-varying delays

Authors :
Zhang, Baoyong
Xu, Shengyuan
Zong, Guangdeng
Zou, Yun
Source :
IEEE Transactions on Circuits and Systems-I-Regular Papers. June, 2009, Vol. 56 Issue 6, p1241, 7 p.
Publication Year :
2009

Abstract

This paper provides new delay-dependent conditions that guarantee the robust exponential stability of stochastic Hopfield type neural networks with time-varying delays and parameter uncertainties. Both the cases of the time-varying delays which are differentiable and may not be differentiable are considered. The stability conditions are derived by using the recently developed free-weighting matrices technique and expressed in terms of linear matrix inequalities. Numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria. It is shown that the proposed stability results are less conservative than some previous ones in the literature. Index Terms--Delay-dependent conditions, Hopfield neural networks, robust exponential stability, stochastic neural networks, time-varying delays.

Details

Language :
English
ISSN :
15498328
Volume :
56
Issue :
6
Database :
Gale General OneFile
Journal :
IEEE Transactions on Circuits and Systems-I-Regular Papers
Publication Type :
Academic Journal
Accession number :
edsgcl.203334821