Ping Chen, Chuangxia Huang, Xiaolin Liang
Abstract:
In this article, we consider a model that
describes the dynamics of Cohen-Grossberg neural networks with
unbounded distributed delays, whose state variable are governed
by stochastic non-linear integro-differential equations.
Without assuming the smoothness, monotonicity and boundedness
of the activation functions, by constructing suitable Lyapunov
functional, employing the semi-martingale convergence theorem
and some inequality, we obtain some sufficient criteria to check
the almost exponential stability of networks.
Submitted December 21, 2009. Published March 26, 2010.
Math Subject Classifications: 34F05, 93E15.
Key Words: Cohen-Grossberg neural networks; stochastic; distributed delays;
almost sure exponential stability; Lyapunov functional.
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Ping Chen College of Mathematics and Computing Science Changsha University of Science and Technology Changsha, Hunan 410114, China email: chenping04@gmail.com |
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Chuangxia Huang College of Mathematics and Computing Science Changsha University of Science and Technology Changsha, Hunan 410114, China email: huangchuangxia@sina.com.cn |
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Xiaolin Liang College of Mathematics and Computing Science Changsha University of Science and Technology Changsha, Hunan 410114, China email: liang@csust.edu.cn |
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