DYNAMICS OF NEW CLASS OF HOPFIELD NEURAL NETWORKS WITH TIME-VARYING AND DISTRIBUTED DELAYS

查看全文 作　　者：Adnene [1]ARBI;Farouk [2]CHERIF;Chaouki [1]AOUITI;Abderrahmen [1]TOUATI

机构地区：[1]Department of Mathematics,Facultd des Sciences de Bizerte,University of Carthage,Jarzouna 7021,Bizerte,Tunisia;[2]Department of Computer Science,ISSATS,Laboratory of Math Physics,University of Sousse,Specials Functions and Applications LR11ES35,ecole suprieure des sciences et de technologie,Sousse 4002,Tunisia

出　　处：《Acta Mathematica Scientia》索引2016年第36卷第3期,共22页

摘　　要：In this paper,we investigate the dynamics and the global exponential stability of a new class of Hopfield neural network with time-varying and distributed delays.In fact,the properties of norms and the contraction principle are adjusted to ensure the existence as well as the uniqueness of the pseudo almost periodic solution,which is also its derivative pseudo almost periodic.This results are without resorting to the theory of exponential dichotomy.Furthermore,by employing the suitable Lyapunov function,some delay-independent sufficient conditions are derived for exponential convergence.The main originality lies in the fact that spaces considered in this paper generalize the notion of periodicity and almost periodicity.Lastly,two examples are given to demonstrate the validity of the proposed theoretical results. 关键词：时滞HOPFIELD神经网络时变时滞和分布 LYAPUNOV函数动力学全局指数稳定性指数二分法充分条件

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DYNAMICS OF NEW CLASS OF HOPFIELD NEURAL NETWORKS WITH TIME-VARYING AND DISTRIBUTED DELAYS

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