A new approach based on discrete-time high-order neural networks with delays and impulses

被引：14

作者：

Wang, Jinling ^{[1
]}

Jiang, Haijun ^{[1
]}

Ma, Tianlong ^{[2
]}

Hu, Cheng ^{[1
]}

机构：

[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China

[2] Qinghai Univ, Coll Basic Res, Xining 810016, Qinghai, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2018年 / 355卷 / 11期

关键词：

GLOBAL EXPONENTIAL STABILITY; FIXED-POINTS; SYSTEMS; SYNCHRONIZATION; CONVERGENCE; EXISTENCE; CRITERIA;

D O I：

10.1016/j.jfranklin.2018.04.032

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is concerned with the stability of discrete-time high-order neural networks (HONNs) with delays and impulses. Without applying the Lyapunov function, some sufficient conditions, which ensure the exponential stability and asymptotic stability of considered networks involving delays and impulses, are derived based on the fixed point theory. Finally, several numerical examples are given to demonstrate the effectiveness of the obtained results. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：4708 / 4726

页数：19

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