Global synchronization in an array of delayed neural networks with hybrid coupling

Jinde Cao, Guanrong Chen, Ping Li

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

353 Citations (Scopus)

Abstract

In this paper, we propose and study a general array model of coupled delayed neural networks with hybrid coupling, which is composed of constant coupling, discrete-delay coupling, and distributed-delay coupling. Based on the Lyapunov functional method and Kronecker product properties, several sufficient conditions are established to ensure global exponential synchronization based on the design of the coupling matrices, the inner linking matrices, and/or some free matrices representing the relationships between the system matrices. The conditions are expressed within the framework of linear matrix inequalities, which can be easily computed by the interior-point method. In addition, a typical chaotic cellular neural network is used as the node in the array to illustrate the effectiveness and advantages of the theoretical results. © 2008 IEEE.
Original languageEnglish
Pages (from-to)488-498
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume38
Issue number2
DOIs
Publication statusPublished - Apr 2008

Research Keywords

  • Delayed neural network
  • Distributed-delay coupling
  • Global exponential synchronization
  • Hybrid coupling
  • Kronecker product
  • Lyapunov-Krasovskii functional

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