The characteristics method to study global exponential stability of delayed inertial neural networks

被引：0
|
作者：
Wang, Wentao [1 ]
Wu, Jihui [1 ]
Chen, Wei [2 ]
机构：
[1] Shanghai Univ Engn Sci, Sch Math Phys & Stat, Shanghai 201620, Peoples R China
[2] Shanghai Lixin Univ Accounting & Finance, Sch Stat & Math, Shanghai 201209, Peoples R China
来源：
MATHEMATICS AND COMPUTERS IN SIMULATION | 2025年 / 232卷
关键词：
Inertial neural networks; Global exponential stability; Delay; Characteristics method; Decay and delay-dependent; Decay and delay-independent; SYNCHRONIZATION; DYNAMICS; CHAOS; MODEL;
D O I：
10.1016/j.matcom.2024.12.021
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we address the issue of global exponential stability for a class of delayed inertial neural networks (DINNs). Employing the characteristics method, we derive several sufficient conditions, which are both decay and delay-dependent as well as decay and delay-independent, to guarantee the global exponential stability of the given neural networks. Lastly, we present three numerical examples to highlight the advantages of our novel results.
引用
收藏
页码：91 / 101
页数：11
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