Global exponential stability in the mean square of stochastic cohen-grossberg neural networks with time-varying and continuous distributed delays

Authors:
Tian Liang;Yongqing Yang;Manfeng Hu;Yang Liu;Li Li
Affiliations:
Key Laboratory of Advanced Process Control for Light Industry, (Ministry of Education), School of Science, Jiangnan University, Wuxi, P.R. China;Key Laboratory of Advanced Process Control for Light Industry, (Ministry of Education), School of Science, Jiangnan University, Wuxi, P.R. China;Key Laboratory of Advanced Process Control for Light Industry, (Ministry of Education), School of Science, Jiangnan University, Wuxi, P.R. China;Key Laboratory of Advanced Process Control for Light Industry, (Ministry of Education), School of Science, Jiangnan University, Wuxi, P.R. China;Key Laboratory of Advanced Process Control for Light Industry, (Ministry of Education), School of Science, Jiangnan University, Wuxi, P.R. China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

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Abstract

In this paper, the global exponential stability in the mean square of stochastic Cohen-Grossberg neural networks (SCGNNS) with mixed delays is studied. By applying the Lyapunov function, stochastic analysis technique and inequality techniques, some sufficient conditions are obtained to ensure the exponential stability in the mean square of the SCGNNS. An example is given to illustrate the theoretical results.