Parameters estimation and synchronization of uncertain coupling recurrent dynamical neural networks with time-varying delays based on adaptive control

被引：8

作者：

Zheng, Mingwen ^{[1
,3
]}

Li, Lixiang ^{[2
]}

Peng, Haipeng ^{[2
]}

Xiao, Jinghua ^{[1
,4
]}

Yang, Yixian ^{[2
]}

Zhao, Hui ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China

[2] Beijing Univ Posts & Telecommun, Informat Secur Ctr, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China

[3] Shandong Univ Technol, Sch Sci, Zibo 255000, Peoples R China

[4] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China

来源：

NEURAL COMPUTING & APPLICATIONS | 2018年 / 30卷 / 07期

基金：

中国国家自然科学基金;

关键词：

CRDNNs; Parameters estimation; Adaptive controller; Lyapunov function; MARKOVIAN JUMPING PARAMETERS; FEEDBACK-CONTROL SYSTEMS; ROBUST POLE ASSIGNMENT; EXPONENTIAL SYNCHRONIZATION; PROJECTIVE SYNCHRONIZATION; LAG SYNCHRONIZATION; UNKNOWN-PARAMETERS; COMPLEX NETWORKS; CHAOTIC SYSTEMS; MIXED DELAYS;

D O I：

10.1007/s00521-016-2822-6

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 mainly studies the parameters estimation and synchronization of coupling recurrent dynamical neural networks (CRDNNs). Here, the weights and coupling parameters of CRDNNs are unknown. By designing a new adaptive controller and parameters update rules, a simple linear matrix inequality criterion is established for the parameters estimation and synchronization problem of CRDNNs. We prove the conclusion by constructing a suitable Lyapunov function. A numerical simulation is given to show the effectiveness of the conclusion.

引用

页码：2217 / 2227

页数：11

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