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Entropy 2013, 15(8), 3265-3276; doi:10.3390/e15083355

Synchronization of a Class of Fractional-Order Chaotic Neural Networks

1
School of Automation, Chongqing University, Chongqing 400044, China
2
School of Mathematics, Anhui University, Hefei 230039, China
3
Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0001, South Africa
*
Author to whom correspondence should be addressed.
Received: 5 June 2013 / Revised: 3 August 2013 / Accepted: 5 August 2013 / Published: 14 August 2013
(This article belongs to the Special Issue Dynamical Systems)
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Abstract

The synchronization problem is studied in this paper for a class of fractional-order chaotic neural networks. By using the Mittag-Leffler function, M-matrix and linear feedback control, a sufficient condition is developed ensuring the synchronization of such neural models with the Caputo fractional derivatives. The synchronization condition is easy to verify, implement and only relies on system structure. Furthermore, the theoretical results are applied to a typical fractional-order chaotic Hopfield neural network, and numerical simulation demonstrates the effectiveness and feasibility of the proposed method.
Keywords: synchronization; fractional-order; chaotic neural networks; linear feedback control synchronization; fractional-order; chaotic neural networks; linear feedback control
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chen, L.; Qu, J.; Chai, Y.; Wu, R.; Qi, G. Synchronization of a Class of Fractional-Order Chaotic Neural Networks. Entropy 2013, 15, 3265-3276.

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