Delay-dependent and order-dependent conditions for stability and stabilization of fractional-order memristive neural networks with time- varying delays

被引：9
作者：
Jin, Xiao-Chuang [1 ,2 ]
Lu, Jun-Guo [1 ,2 ]
Zhang, Qing-Hao [1 ,2 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
来源：
NEUROCOMPUTING | 2023年 / 522卷
基金：
中国国家自然科学基金;
关键词：
Fractional -order nonlinear system; Memristive neural network; Time -varying delay; Stability; Stabilization; SYNCHRONIZATION; DESIGN;
D O I：
10.1016/j.neucom.2022.12.006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The stability and stabilization problems of fractional-order memristive neural networks with time -varying delays are addressed. Based on Jensen-based integral inequalities, novel delay-dependent and order-dependent stability conditions for fractional-order memristive neural networks with time -varying delays are established. The proposed stability criterion is in terms of linear matrix inequalities and is easy to be verified and applied. Then, a linear feedback control law that stabilizes fractional -order memristive neural networks with time-varying delays is designed by utilizing the obtained stability conditions. Two numerical examples are used to illustrate the effectiveness and less conservativeness of the proposed results.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码：53 / 63
页数：11
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