4.7 Article

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

期刊

NEURAL NETWORKS
卷 86, 期 -, 页码 90-101

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2016.11.001

关键词

Complex-valued Cohen-Grossberg neural networks; Exponential synchronization; Adaptive control

资金

  1. National Natural Science Foundation of China [61273021, 61403051]
  2. Program of Chongqing Innovation Team Project in University [CXTDX201601022]
  3. Natural Science Foundation Project of CQ CSTC [cstc 2014jcyjA00019]
  4. Technology Research Foundation of Chongqing Educational Committee [KJ1500312]
  5. Natural Foundation advanced research of CQNU [14XYY028]

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据