Projective Synchronization of Nonidentical Fractional-Order Memristive Neural Networks

Chong Chen and Zhixia Ding

Discrete Dynamics in Nature and Society, 2019, vol. 2019, 1-11

Abstract:

This paper investigates projective synchronization of nonidentical fractional-order memristive neural networks (NFMNN) via sliding mode controller. Firstly, based on the sliding mode control theory, a new fractional-order integral sliding mode controller is designed to ensure the occurrence of sliding motion. Furthermore, according to fractional-order differential inequalities and fractional-order Lyapunov direct method, the trajectories of the system converge to the sliding mode surface to carry out sliding mode motion, and some sufficient criteria are obtained to achieve global projective synchronization of NFMNN. In addition, the conclusions extend and improve some previous works on the synchronization of fractional-order memristive neural networks (FMNN). Finally, a simulation example is given to verify the effectiveness and correctness of the obtained results.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:8743482

DOI: 10.1155/2019/8743482

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