Pullback attractor of Hopfield neural networks with multiple time-varying delays

被引:0
作者
Zhou, Qinghua [1 ]
Wan, Li [2 ]
Fu, Hongbo [2 ]
Zhang, Qunjiao [2 ]
机构
[1] Qingdao Univ Sci & Technol, Sch Math & Phys, Qingdao 266061, Shandong, Peoples R China
[2] Wuhan Text Univ, Engn Technol Res Ctr Hubei Prov Clothing Informat, Ctr Appl Math & Interdisciplinary Sci, Res Ctr Nonlinear Sci,Sch Math & Phys, Wuhan 430073, Hubei, Peoples R China
来源
AIMS MATHEMATICS | 2021年 / 6卷 / 07期
基金
中国国家自然科学基金;
关键词
Hopfield neural network; multiple time-varying delays; pullback attractor; linear matrix inequality; STABILITY ANALYSIS; DIFFERENTIAL-EQUATIONS; ROBUST STABILITY; BIFURCATION; STABILIZATION; DYNAMICS; CHAOS;
D O I
10.3934/math.2021435
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper deals with the attractor problem of Hopfield neural networks with multiple time-varying delays. The mathematical expression of the networks cannot be expressed in the vector-matrix form due to the existence of the multiple delays, which leads to the existence condition of the attractor cannot be easily established by linear matrix inequality approach. We try to derive the existence conditions of the linear matrix inequality form of pullback attractor by employing Lyapunov-Krasovskii functional and inequality techniques. Two examples are given to demonstrate the effectiveness of our theoretical results and illustrate the conditions of the linear matrix inequality form are better than those of the algebraic form.
引用
收藏
页码:7441 / 7455
页数:15
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