Synchronization in delayed Cohen-Grossberg neural networks with bounded external inputs

Chun Hsien Li, Suh Yuh Yang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this paper, we study the drive-response-type synchronization in the delayed Cohen-Grossberg neural networks with bounded external inputs. The connection time delays between neurons can be of discrete or distributed form. By using the Lyapunov functional method, we establish three criteria all independent of the time delays for ensuring the occurrence of synchronization with exponential rates. Generally speaking, we prove that the exponential synchronization occurs provided some certain weighted sum of the connection and coupling strengths with other system parameters is positive enough no matter that the connection time delay is of discrete or distributed form. Our criteria improve and extend some existing ones. Furthermore, several concrete examples are provided to show that the three criteria do not include one another. Numerical simulations are also given to demonstrate the theoretical results.

Original languageEnglish
Pages (from-to)178-200
Number of pages23
JournalIMA Journal of Applied Mathematics (Institute of Mathematics and Its Applications)
Volume74
Issue number2
DOIs
StatePublished - 2009

Keywords

  • Cohen-Grossberg neural networks
  • Discrete time delays
  • Distributed time delays
  • Exponential synchronization
  • Lyapunov functionals

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