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.
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页码：1180 / +
页数：3
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