Synchronization for fractional-order reaction?diffusion competitive neural networks with leakage and discrete delays q

被引：36
作者：
Yang, Shuai [1 ]
Jiang, Haijun [1 ]
Hu, Cheng [1 ]
Yu, Juan [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
来源：
NEUROCOMPUTING | 2021年 / 436卷
基金：
中国国家自然科学基金;
关键词：
Fractional calculus; Delayed competitive neural network; Reaction?diffusion; Synchronization; GLOBAL EXPONENTIAL STABILITY; MITTAG-LEFFLER SYNCHRONIZATION; OUTER-SYNCHRONIZATION; COMPLEX NETWORKS; MULTISTABILITY; TERMS;
D O I：
10.1016/j.neucom.2021.01.009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is concerned with the synchronization of fractional-order competitive neural networks with reaction-diffusion terms and time delays. A novel method that combines the fractional-order Lyapunov theorem with M-matrix theory is utilized to cope with synchronization for the addressed networks. Based on such approach and developing two different controllers, some sufficient criteria are derived to guarantee global synchronization by employing the properties about Mittag-Leffler and trigonometric functions, comparison principle as well as the method of contradiction. Finally, a numerical example is provided to show the effectiveness of the established result. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码：47 / 57
页数：11
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