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Synchronization of a class of fractional-order chaotic neural networks. (English) Zbl 1339.34060
Summary: The synchronization problem is studied 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.

MSC:
34D06 Synchronization of solutions to ordinary differential equations
34H10 Chaos control for problems involving ordinary differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
93B52 Feedback control
34A08 Fractional ordinary differential equations and fractional differential inclusions
34C28 Complex behavior and chaotic systems of ordinary differential equations
33E12 Mittag-Leffler functions and generalizations
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