Delta-Differentiable Weighted Pseudo-Almost Automorphicity on Time-Space Scales for a Novel Class of High-Order Competitive Neural Networks with WPAA Coefficients and Mixed Delays

被引：19

作者：

Arbi, Adnene ^{[1
,2
]}

Alsaedi, Ahmed ^{[3
]}

Cao, Jinde ^{[4
,5
,6
]}

机构：

[1] Univ Kairouan, Dept Math Phys & Comp Sci, Higher Inst Appl Sci & Technol Kairouan, Kairouan 3100, Tunisia

[2] Univ Carthage, Lab Engn Math LR01ES13, Tunisia Polytech Sch, El Khawarizmi St, Carthage 2078, Tunisia

[3] King Abdulaziz Univ, Dept Math, Nonlinear Anal & Appl Math NAAM Res Grp, Jeddah 21589, Saudi Arabia

[4] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China

[5] Southeast Univ, Res Ctr Complex Syst & Network Sci, Nanjing 210096, Jiangsu, Peoples R China

[6] King Abdulaziz Univ, Dept Math, Fac Sci, Jeddah 21589, Saudi Arabia

来源：

NEURAL PROCESSING LETTERS | 2018年 / 47卷 / 01期

关键词：

Time scales; High-order competitive neural networks; Weighted pseudo-almost automorphic solution; Global exponential stability; Leakage delays; EXISTENCE; EQUATIONS; STABILITY;

D O I：

10.1007/s11063-017-9645-z

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, we consider a novel class of high-order competitive neural networks with mixed delays. Different from the previous literature, we study the existence and exponential stability of weighted pseudo-almost automorphic on time-space scales solutions for the suggested system. Our method is mainly based on the Banach's fixed point theorem, the theory of calculus on time scales and the Lyapunov-Krasovskii functional method. Moreover, a numerical example is given to show the effectiveness of the main results.

引用

页码：203 / 232

页数：30

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