Mittag-Leffler stability and stabilization of delayed fractional-order memristive neural networks based on a new Razumikhin-type theorem

被引：12

作者：

Zhang, Shuailei ^{[1
]}

Tang, Meilan ^{[1
]}

Liu, Xinge ^{[1
]}

Zhang, Xian-Ming ^{[2
]}

机构：

[1] Cent South Univ, Sch Math & Stat, Changsha 410083, Hunan, Peoples R China

[2] Swinburne Univ Technol, Sch Sci Comp & Engn Technol, Melbourne, Vic 3122, Australia

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2024年 / 361卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Halanay inequality; Memristive neural networks; Razumikhin-type theorem; Mittag-Leffler stability; Fractional-order; SYNCHRONIZATION; SYSTEMS; INEQUALITY; PASSIVITY; CRITERIA;

D O I：

10.1016/j.jfranklin.2024.01.008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The Mittag-Leffler stability and stabilization of delayed fractional -order memristive neural networks(DFMNNs) are investigated in this paper. First, two new fractional Halanay inequalities are established by solving two fractional -order non -autonomous differential inequalities. Next, by using the proposed fractional Halanay inequalities, a novel Razumikhin-type theorem for Mittag-Leffler stability of delayed fractional -order systems is presented, which is an extension of the so-called Razumikhin theorem for integer -order delayed differential systems. Applying the Razumikhin-type theorem to the DFMNNs, several Mittag-Leffler stability and stabilization criteria are obtained. Finally, the validity of the proposed results is shown by two numerical examples.

引用

页码：1211 / 1226

页数：16

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