Synchronization of a Class of Fractional-Order Chaotic Neural Networks

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...

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Bibliographic Details
Main Authors: Yi Chai, Jianfeng Qu, Liping Chen, Guoyuan Qi, Ranchao Wu
Format: Article
Language:English
Published: MDPI AG 2013-08-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/15/8/3265
Description
Summary: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.
ISSN:1099-4300