Adaptive exponential synchronization of complex-valued Cohen-Grossberg neural networks with known and unknown parameters

被引：63
作者：
Hu, Jin [1 ]
Zeng, Chunna [2 ]
机构：
[1] Chongqing Jiaotong Univ, Dept Math, Chongqing, Peoples R China
[2] Chongqing Normal Univ, Coll Math Sci, Chongqing, Peoples R China
来源：
NEURAL NETWORKS | 2017年 / 86卷
基金：
中国国家自然科学基金;
关键词：
Complex-valued Cohen-Grossberg neural networks; Exponential synchronization; Adaptive control; TIME-VARYING DELAYS; STABILITY ANALYSIS; OPTIMIZATION; SYSTEMS;
D O I：
10.1016/j.neunet.2016.11.001
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The complex-valued Cohen-Grossberg neural network is a special kind of complex-valued neural network. In this paper, the synchronization problem of a class of complex-valued Cohen-Grossberg neural networks with known and unknown parameters is investigated. By using Lyapunov functionals and the adaptive control method based on parameter identification, some adaptive feedback schemes are proposed to achieve synchronization exponentially between the drive and response systems. The results obtained in this paper have extended and improved some previous works on adaptive synchronization of Cohen-Grossberg neural networks. Finally, two numerical examples are given to demonstrate the effectiveness of the theoretical results. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码：90 / 101
页数：12
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