On the synchronization of neural networks containing time-varying delays and sector nonlinearity

Jun Juh Yan, Jui Sheng Lin, Meei Ling Hung, Teh Lu Liao

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme.

Original languageEnglish
Pages (from-to)70-77
Number of pages8
JournalPhysics Letters, Section A: General, Atomic and Solid State Physics
Volume361
Issue number1-2
DOIs
Publication statusPublished - 2007 Jan 22

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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