东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (4): 475-478.DOI: -

• 论著 • 上一篇    下一篇

一类混合时变时滞混沌神经网络自适应同步研究

刘兆冰;张化光;杨东升;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-04-15 发布日期:2013-06-22
  • 通讯作者: Liu, Z.-B.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60728307);;

Adaptive synchronization of a class of chaotic neural networks with mixed time-varying delays

Liu, Zhao-Bing (1); Zhang, Hua-Guang (1); Yang, Dong-Sheng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-04-15 Published:2013-06-22
  • Contact: Liu, Z.-B.
  • About author:-
  • Supported by:
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摘要： 基于微分方程的拉萨尔不变集原理和自适应动态反馈控制技术,研究了一类带有完全未知参数和混合时变时滞的混沌神经网络的自适应同步问题,给出了保证两个具有相同结构但具有完全未知参数的时滞混沌神经网络同步的控制律的设计方法.在此自适应控制律的作用下,达到了同步与参数辨识同时进行的目的.所设计的控制律简单,易于实现.仿真示例验证了所提方法的有效性.

关键词: 未知参数, 混合时变时滞, 混沌神经网络, 自适应同步, 参数辨识

Abstract: Based on Lasalle invariance theorem of differential equations and adaptive dynamical feedback technique, the adaptive synchronization of a class of chaotic neural networks with fully unknown parameters and mixed time-varying delays is investigated, and as a result, a well-designed method is given to ensure the synchronization of two chaotic neural networks which are of the same structure and fully unknown parameters. Under the action of the adaptive control law, the synchronization and parametric identification can be done simultaneously. The controller designed is simple and easy to implement. Simulation examples are given to verify the effectiveness of the proposed method.

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