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STABILITY FOR THE MIX-DELAYED COHEN-GROSSBERG NEURAL NETWORKS WITH NONLINEAR IMPULSE 被引量:2

STABILITY FOR THE MIX-DELAYED COHEN-GROSSBERG NEURAL NETWORKS WITH NONLINEAR IMPULSE
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摘要 In this paper,the authors are concerned with the stability of the mix-delayed Cohen-Grossbergneural networks with nonlinear impulse by the nonsmooth analysis.Some novel sufficientconditions are obtained for the existence and the globally asymptotic stability of the unique equilibriumpoint,which include the well-known results on some impulsive systems and non-impulsive systems asits particular cases.The authores also analyze the globally exponential stability of the equilibriumpoint.Two examples are exploited to illustrate the feasibility and effectiveness of our results.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2010年第3期665-680,共16页 系统科学与复杂性学报(英文版)
基金 supported by the National Natural Science Foundation of China under Grant No. 10872014 the Natural Science Foundation of Fujian Province of China under Grant No. S0750008 partially supported by UTPA Faculty Research Council under Grant No. 119100
关键词 Asymptotic stability equilibrium point Lyapunov method neural networks nonlinear impulses nonsmooth analysis. 全局指数稳定性 脉冲神经网络 非线性脉冲 时滞 混合 全局渐近稳定 脉冲系统 非光滑分析
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