数学物理学报(英文版) ›› 2016, Vol. 36 ›› Issue (3): 891-912.doi: 10.1016/S0252-9602(16)30048-0

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

Adnène ARBI1, Farouk CHÉRIF2, Chaouki AOUITI1, Abderrahmen TOUATI1   

  1. 1. Department of Mathematics, Faculté 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 LR11 ES35, Ecole Supérieure des Sciences et de Technologie, Sousse 4002, Tunisia
  • 收稿日期:2015-01-25 修回日期:2015-07-17 出版日期:2016-06-25 发布日期:2016-06-25
  • 通讯作者: Adnène ARBI,E-mail:adnen.arbi@enseignant.edunet.tn E-mail:adnen.arbi@enseignant.edunet.tn
  • 作者简介:Farouk CHÉRIF,E-mail:faroukcheriff@yahoo.fr;Chaouki AOUITI,E-mail:chaouki.aouiti@fsb.rnu.tn;Abderrahmen TOUATI,E-mail:Abder.Touati@fsb.rnu.tn

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

Adnène ARBI1, Farouk CHÉRIF2, Chaouki AOUITI1, Abderrahmen TOUATI1   

  1. 1. Department of Mathematics, Faculté 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 LR11 ES35, Ecole Supérieure des Sciences et de Technologie, Sousse 4002, Tunisia
  • Received:2015-01-25 Revised:2015-07-17 Online:2016-06-25 Published:2016-06-25
  • Contact: Adnène ARBI,E-mail:adnen.arbi@enseignant.edunet.tn E-mail:adnen.arbi@enseignant.edunet.tn

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: delayed functional differential equations, neural networks, pseudo-almost periodic solution, global exponential stability, time-varying and distributed delays, fixed point theorem

Abstract:

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.

Key words: delayed functional differential equations, neural networks, pseudo-almost periodic solution, global exponential stability, time-varying and distributed delays, fixed point theorem

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