Exponential stability of stochastic interval cellular neural networks

Authors:
Jinfang Han;Zhiyong Liu
Affiliations:
Inst. of Eng. Math., Hebei University of Science and Technilogy, Shijiazhuang, Hebei, P.R. China;School of International Commerce, Tianjin Foreign Studies University, Tianjin, P.R. China
Venue:
ICNC'09 Proceedings of the 5th international conference on Natural computation
Year:
2009

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Abstract

In this paper, the exponential stability problem of a class of stochastic interval delayed cellular neural networks is studied. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the Itô formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literature are generalized.