Positivity and Stability of Fractional-Order Coupled Neural Network with Time-Varying Delays

被引：0

作者：

Gong, Jiyun ^{[1
]}

Qiu, Hongling ^{[1
]}

Shen, Jun ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 211106, Peoples R China

来源：

ELECTRONICS | 2023年 / 12卷 / 23期

基金：

中国国家自然科学基金;

关键词：

positivity; stability; fractional order; neural networks; time-varying delay; LINEAR-SYSTEMS;

D O I：

10.3390/electronics12234782

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 brief paper analyzes the positivity and asymptotic stability of incommensurate fractional-order coupled neural networks (FOCNNs) with time-varying delays. Under a reasonable assumption about the activation functions of neurons, a sufficient and necessary condition is proposed to guarantee that FOCNNs are positive systems. Furthermore, the sufficient and necessary condition ensuring the asymptotic stability of FOCNNs is also given via introducing a linear auxiliary system. Finally, a simulation experiment was carried out to justify the effectiveness of the derived results.

引用

页数：11

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