Synchronization between Two Different Chaotic Neural Networks with Fully Unknown Parameters

被引：0
|
作者：
Xie, Yinghui [1 ,3 ]
Sun, Zengqi [1 ,2 ]
Wang, Fushan [3 ]
机构：
[1] Tsinghua Univ, Dept Comp Sci & Technol, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China
[2] Natl Lab Space Intelligent Control, Beijing 100084, Peoples R China
[3] ShenYang Artillery Inst, Dept Fdn, Shenyang 110163, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 2, PROCEEDINGS | 2009年 / 5552卷
基金：
中国国家自然科学基金;
关键词：
Synchronization; Chaotic neural networks; Fully unknown parameters; Different; Time-delay; GLOBAL EXPONENTIAL STABILITY; ADAPTIVE SYNCHRONIZATION; TIME-DELAY; ATTRACTORS; SYSTEMS;
D O I：
暂无
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 presents the adaptive synchronization between two different chaotic neural networks with fully unknown parameters and with time-delay. Based on the Lyapunov stability theory, the delay-dependent adaptive synchronization controller is designed to asymptotically synchronizing two different, chaotic neural networks. A parameter update law is also given. The designed controller can easily be implemented in practice. An illustrative example is given to demonstrate the effectiveness of the present method.
引用
收藏
页码：1180 / +
页数：3
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