Synchronization of neural networks by decentralized feedback control

Chao Jung Cheng; Teh Lu Liao; Jun Juh Yan; Chi Chuan Hwang

doi:10.1016/j.physleta.2005.01.082

Synchronization of neural networks by decentralized feedback control

Chao Jung Cheng
, Teh Lu Liao
, Jun Juh Yan
, Chi Chuan Hwang

Department of Engineering Science

Research output: Contribution to journal › Article › peer-review

50 Citations (Scopus)

Abstract

This Letter deals with the synchronization problem of a class of neural networks with/without time delays. Based on the drive-response concept and the Lyapunov stability theorem, a delay-independent and decentralized control law is derived to achieve the exponential synchronization. Two illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.

Original language	English
Pages (from-to)	28-35
Number of pages	8
Journal	Physics Letters, Section A: General, Atomic and Solid State Physics
Volume	338
Issue number	1
DOIs	https://doi.org/10.1016/j.physleta.2005.01.082
Publication status	Published - 2005 Apr 18

All Science Journal Classification (ASJC) codes

General Physics and Astronomy

Access to Document

10.1016/j.physleta.2005.01.082

Cite this

@article{ecee6fd0122d4b5a98668e899d3c9d91,

title = "Synchronization of neural networks by decentralized feedback control",

abstract = "This Letter deals with the synchronization problem of a class of neural networks with/without time delays. Based on the drive-response concept and the Lyapunov stability theorem, a delay-independent and decentralized control law is derived to achieve the exponential synchronization. Two illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.",

author = "Cheng, \{Chao Jung\} and Liao, \{Teh Lu\} and Yan, \{Jun Juh\} and Hwang, \{Chi Chuan\}",

year = "2005",

month = apr,

day = "18",

doi = "10.1016/j.physleta.2005.01.082",

language = "English",

volume = "338",

pages = "28--35",

journal = "Physics Letters, Section A: General, Atomic and Solid State Physics",

issn = "0375-9601",

publisher = "Elsevier BV",

number = "1",

}

TY - JOUR

T1 - Synchronization of neural networks by decentralized feedback control

AU - Cheng, Chao Jung

AU - Liao, Teh Lu

AU - Yan, Jun Juh

AU - Hwang, Chi Chuan

PY - 2005/4/18

Y1 - 2005/4/18

N2 - This Letter deals with the synchronization problem of a class of neural networks with/without time delays. Based on the drive-response concept and the Lyapunov stability theorem, a delay-independent and decentralized control law is derived to achieve the exponential synchronization. Two illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.

AB - This Letter deals with the synchronization problem of a class of neural networks with/without time delays. Based on the drive-response concept and the Lyapunov stability theorem, a delay-independent and decentralized control law is derived to achieve the exponential synchronization. Two illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.

UR - https://www.scopus.com/pages/publications/15744378840

UR - https://www.scopus.com/pages/publications/15744378840#tab=citedBy

U2 - 10.1016/j.physleta.2005.01.082

DO - 10.1016/j.physleta.2005.01.082

M3 - Article

AN - SCOPUS:15744378840

SN - 0375-9601

VL - 338

SP - 28

EP - 35

JO - Physics Letters, Section A: General, Atomic and Solid State Physics

JF - Physics Letters, Section A: General, Atomic and Solid State Physics

IS - 1

ER -

Synchronization of neural networks by decentralized feedback control

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this