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

页码：1180 / +

页数：3

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