New Results for Exponential Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays

被引：15
|
作者：
Liu, Mei [1 ,2 ]
Jiang, Haijun [2 ]
Hu, Cheng [2 ]
机构：
[1] Zhoukou Normal Univ, Sch Math & Stat, Zhoukou 466001, Peoples R China
[2] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2019年 / 49卷 / 01期
关键词：
Cohen-Grossberg neural network; Time-varying delay; Feedback control; Periodically intermittent control; Memristor; LAG SYNCHRONIZATION; ADAPTIVE SYNCHRONIZATION; DYNAMIC-BEHAVIORS; SYSTEMS; CRITERIA;
D O I：
10.1007/s11063-017-9728-x
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 topic of exponential synchronization for a class of memristive Cohen-Grossberg neural networks with time-varying delays by designing a suitable controller. Through a nonlinear transformation, we obtain an alternative system from the considered memristive Cohen-Grossberg neural networks. Then, by studying the exponential synchronization of the alternative system, we get some novel and effective exponential synchronization criteria for the considered memristive Cohen-Grossberg neural networks. These results generalize some previous known results and remove a few restrictions on control width and time-delays. Finally, numerical simulations are given to present the effectiveness of the theoretical results.
引用
收藏
页码：79 / 102
页数：24
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