Exponential synchronization of a class of chaotic neural networks

Chao-Jung Cheng, Teh-Lu Liao and Chi-Chuan Hwang

Chaos, Solitons & Fractals, 2005, vol. 24, issue 1, 197-206

Abstract: This paper deals with the synchronization problem of a class of chaotic neural networks with or without delays. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks with or without delays. Using the drive-response concept, a control law is derived to achieve the state synchronization of two identical chaotic neural networks. Furthermore, based on the Lyapunov stability method and the Halanay inequality lemma, a delay independent sufficient exponential synchronization condition is derived. The synchronization condition is easy to verify and relies on the connection matrix in the driven networks and the suitable designed controller gain matrix in the response networks. Finally, some illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.

Date: 2005
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:24:y:2005:i:1:p:197-206

DOI: 10.1016/j.chaos.2004.09.022

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