Synchronization control for memristive high-order competitive neural networks with time-varying delay

被引：9
作者：
Gong, Shuqing [1 ,2 ]
Guo, Zhenyuan [1 ]
Wen, Shiping [3 ]
Huang, Tingwen [4 ]
机构：
[1] Hunan Univ, Coll Math & Econometra, Changsha 410082, Hunan, Peoples R China
[2] Changsha Univ Sci & Technol, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Math & Stat, Chengdu 611731, Sichuan, Peoples R China
[4] Texas A&M Univ Qatar, Sci Program, POB 23874, Doha, Qatar
来源：
NEUROCOMPUTING | 2019年 / 363卷
基金：
中国国家自然科学基金;
关键词：
Global exponential synchronization; Memristor; High-order; Competitive neural network; Time-varying delay; GLOBAL EXPONENTIAL SYNCHRONIZATION; STABILITY; DISSIPATIVITY;
D O I：
10.1016/j.neucom.2019.06.049
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 concerns the synchronization problem of memristive high-order competitive neural networks with time-varying delay. First, a novel control scheme with a linear term and a discontinuous term is proposed. Then, based on the Lyapunov stability theory, several criteria with algebraic form or matrix form are derived to ensure global exponential synchronization of the networks by adopting some inequality techniques. Finally, two numerical examples are presented to substantiate the effectiveness of the results. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：295 / 305
页数：11
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