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• W2100071276 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." @default.
• W2100071276 created "2016-06-24" @default.
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• W2100071276 date "2006-02-01" @default.
• W2100071276 modified "2023-10-18" @default.
• W2100071276 title "Exponential synchronization of a class of neural networks with time-varying delays" @default.
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• W2100071276 doi "https://doi.org/10.1109/tsmcb.2005.856144" @default.
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