Finite-time and fixed-time synchronization for a class of memristor-based 
competitive neural networks with different time scales

Zhao, Yong; Ren, Shanshan; Kurths, Jürgen

doi:10.1016/j.chaos.2021.111033

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Finite-time and fixed-time synchronization for a class of memristor-based competitive neural networks with different time scales

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Zhao, Yong
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Ren, Shanshan
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Kurths, Jürgen
Potsdam Institute for Climate Impact Research;

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Zhao, Y., Ren, S., Kurths, J. (2021): Finite-time and fixed-time synchronization for a class of memristor-based competitive neural networks with different time scales. - Chaos, Solitons and Fractals, 148, 111033.
https://doi.org/10.1016/j.chaos.2021.111033

Cite as: https://publications.pik-potsdam.de/pubman/item/item_26425

Abstract

In this paper, finite-time and fixed-time synchronization are considered for a class of memristor-based competitive neural networks(MCNNs) with different time scales. Based on the theory of differential equations with discontinuous right-hand sides, several new sufficient conditions ensuring the finite-time and fixed-time synchronization of MCNNs are obtained by designing proper controllers. Moreover, the settling time is estimated. Finally, a numerical example is given to show the effectiveness and feasibility of our results.