Impulsive generalized high-order recurrent neural networks with mixed delays: Stability and periodicity

被引：23

作者：

Aouiti, Chaouki ^{[1
]}

M'hamdi, Mohammed Salah ^{[1
,2
]}

Cherif, Farouk ^{[3
]}

Alimi, Adel M. ^{[4
]}

机构：

[1] Univ Carthage, Fac Sci Bizerta, Dept Math Math & Applicat UR13ES47, BP W, Zarzouna 7021, Bizerta, Tunisia

[2] Univ Bejaia, Fac Technol, Dept Technol, Bejaia 06000, Algeria

[3] Univ Sousse, Lab Math Phys Specials Funct & Applicat LR11ES35, ISSATS, Dept Comp Sci, Sousse 4002, Tunisia

[4] Univ Sfax, REGIM Lab Res Grp Intelligent Machines, Natl Engn Sch Sfax ENIS, BP 1173, Sfax 3038, Tunisia

来源：

NEUROCOMPUTING | 2018年 / 321卷

关键词：

Piecewise weighted pseudo almost-periodicity; Impulsion; Hopfield neural networks; Mixed delays; GLOBAL EXPONENTIAL STABILITY; EXISTENCE; EQUATIONS; DISCRETE;

D O I：

10.1016/j.neucom.2017.11.037

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, by employing fixed point theorem, generalized Gronwall-Bellman inequality and differential inequality techniques, some sufficient conditions are given for the existence and the exponential stability of the unique piecewise weighted pseudo almost-periodic solution of impulsive high-order recurrent neural networks with time-varying coefficients and mixed delays. An illustrative example is also given in the end of this paper to show the effectiveness of our results. (C) 2017 Published by Elsevier B.V.

引用

页码：296 / 307

页数：12

共 34 条

[1] Existence and Uniqueness of Pseudo Almost-Periodic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays [J].