Synchronization and Parameter Identification for a Class of Chaotic Neural Networks with Time-Varying Delays via Adaptive Control

被引：0
|
作者：
Wang, Zhongsheng [1 ]
Liao, Wudai [2 ]
Yan, Nin [1 ]
机构：
[1] Guangdong Polytech Normal Univ, Coll Automat, Guangzhou 510635, Guangdong, Peoples R China
[2] Zhongyuan Univ Technol, Coll Elect & Informat, Zhengzhou 450007, Peoples R China
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS | 2008年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/ICNC.2008.31
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper aims to present a synchronization and parameter identification scheme for a class of time-varying neural networks. By combining the adaptive control method and the Razumikhin-type Theorem, a novel delay-independent and decentralized linear-feedback control with appropriate updated law is designed to achieve the synchronization and parameter identification The updating law of parameters can be directly constructed. Hopfield neural networks with time-varying delays are given to show the effectiveness of the presented synchronization scheme.
引用
收藏
页码：579 / +
页数：2
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