Stability Analysis of Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays

被引：1

作者：

Gan, Binbin ^{[1
]}

Xu, Biao ^{[1
]}

Chen, Hao ^{[1
]}

机构：

[1] Huaibei Normal Univ, Sch Math Sci, Huaibei 235000, Anhui, Peoples R China

来源：

IEEE ACCESS | 2022年 / 10卷

关键词：

Stability analysis; Delays; Biological neural networks; Neurons; Delay effects; Asymptotic stability; Stability criteria; Global asymptotic stability; Lyapunov functioal; neutral-type Cohen-Grossberg neural networks; time-varying delays; NEUTRAL-TYPE; DEPENDENT STABILITY; GLOBAL STABILITY; SYSTEMS; DISCRETE; CRITERIA;

D O I：

10.1109/ACCESS.2022.3196772

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

By improving a previously introduced Lyapunov functional,this paper addressed the stability issue about neutral-type Cohen-Grossberg neural networks with multiple time-varying delays in the states of neurons and the time derivative of states of neurons, a sufficient condition for global asymptotic stability is obtained. Since the Cohen-Grossberg neural networks considered in this paper is more general than those in the former literature, the obtained result developed stability condition of Cohen-Grossberg neural networks. At the end of the paper, two examples are employed to demonstrate the validity and superiority of the conclusion.

引用

页码：83463 / 83471

页数：9

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