Exponential p-stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays

Authors:
Xiaohu Wang;Qingyi Guo;Daoyi Xu
Affiliations:
Yangtze Center of Mathematics, Sichuan University, Chengdu 610064, Sichuan, PR China;Yangtze Center of Mathematics, Sichuan University, Chengdu 610064, Sichuan, PR China and Department of Mathematics, Kangding Nationality Teacher's College, Kangding 626001, PR China;Yangtze Center of Mathematics, Sichuan University, Chengdu 610064, Sichuan, PR China
Venue:
Mathematics and Computers in Simulation
Year:
2009

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Abstract

In this paper, we study the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. By establishing an L-operator differential inequality with mixed delays and using the properties of M-cone and stochastic analysis technique, we obtain some sufficient conditions ensuring the exponential p-stability of the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. These results generalize a few previous known results and remove some restrictions on the neural networks. Two examples are also discussed to illustrate the efficiency of the obtained results.