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Almost sure exponential stability of neutral stochastic delayed cellular neural networks

Almost sure exponential stability of neutral stochastic delayed cellular neural networks
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摘要 In this paper, almost sure exponential stability of neutral delayed cellular neural networks which are in the noised environment is studied by decomposing the state space to sub-regions in view of the saturation linearity of output functions of neurons of the cellular neural networks. Some algebraic criteria are obtained and easily verified. Some examples are given to illustrate the correctness of the results obtained. In this paper, almost sure exponential stability of neutral delayed cellular neural networks which are in the noised environment is studied by decomposing the state space to sub-regions in view of the saturation linearity of output functions of neurons of the cellular neural networks. Some algebraic criteria are obtained and easily verified. Some examples are given to illustrate the correctness of the results obtained.
出处 《控制理论与应用(英文版)》 EI 2008年第2期195-200,共6页
基金 the National Natural Science Foundation of China (No. 10571036) Tianjin Municipal Education Commission of China(No. 20070405)
关键词 Neutral stochastic delayed cellular neural networks Brownian motion Almost sure exponential stability Neutral stochastic delayed cellular neural networks Brownian motion Almost sure exponential stability
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