Exponential synchronization of a class of neural networks with time-varying delays

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

研究成果: Article同行評審

95 引文 斯高帕斯(Scopus)


This paper aims to present a synchronization scheme for a class of delayed neural networks, which covers the Hopfield neural networks and cellular neural networks with time-varying delays. A feedback control gain matrix is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory, and its exponential synchronization condition can be verified if a certain Hamiltonian matrix with no eigenvalues on the imaginary axis. This condition can avoid solving an algebraic Riccati equation. Both the cellular neural networks and Hopfield neural networks with time-varying delays are given as examples for illustration.

頁(從 - 到)209-215
期刊IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
出版狀態Published - 2006 二月

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 軟體
  • 資訊系統
  • 人機介面
  • 電腦科學應用
  • 電氣與電子工程


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