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Exponential synchronization of a class of neural networks with time-varying delays
Chao-Jung Cheng; Teh-Lu Liao; Jun-Juh Yan; Chi-Chuan Hwang;
Systems, Man, and Cybernetics, Part B, IEEE Transactions on
Volume 36,
Issue 1,
Feb. 2006
Page(s):209
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215
Abstract:
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.
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