Globally Exponential Stability for Stochastic Delayed Neural Networks Under Impulsive Control
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作者:
Li, Xiao-ai
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Cent S Univ, Sch Math Sci & Comp Technol, Changsha 410007, Hunan, Peoples R ChinaCent S Univ, Sch Math Sci & Comp Technol, Changsha 410007, Hunan, Peoples R China
Li, Xiao-ai
[1
]
Zou, Jie-zhong
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Cent S Univ, Sch Math Sci & Comp Technol, Changsha 410007, Hunan, Peoples R ChinaCent S Univ, Sch Math Sci & Comp Technol, Changsha 410007, Hunan, Peoples R China
Zou, Jie-zhong
[1
]
机构:
[1] Cent S Univ, Sch Math Sci & Comp Technol, Changsha 410007, Hunan, Peoples R China
In this paper, the dynamic behaviors of a class of stochastic neural networks with time-varying delays and fixed moments of impulsive effect are considered. A new sufficient condition has been presented ensuring the global exponential stability for the equilibrium point by using Lyapunov functional method, stochastic theory and inequality technique. The results established here extend those given previously in the literatures. Finally, an example with simulation is given to show the effectiveness of the obtained results. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]