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Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks

1
School of Mathematics and Computational Science, Anqing Normal University, Anqing 246011, China
2
School of Mathematics, Southeast University, Nanjing 210096, China
3
Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
4
Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(1), 54; https://doi.org/10.3390/e20010054
Received: 13 December 2017 / Revised: 7 January 2018 / Accepted: 8 January 2018 / Published: 12 January 2018
(This article belongs to the Special Issue Research Frontier in Chaos Theory and Complex Networks)
This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasibility and effectiveness of the proposed system are validated through numerical simulations. View Full-Text
Keywords: synchronization; comparison theorem; time-delay; fractional order; complex valued neural networks synchronization; comparison theorem; time-delay; fractional order; complex valued neural networks
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Zhang, W.; Cao, J.; Chen, D.; Alsaadi, F.E. Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks. Entropy 2018, 20, 54.

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