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Research Article | Open Access

Quasi-projective and finite-time synchronization of fractional-order memristive complex-valued delay neural networks via hybrid control

Jiaqing Zhu1Guodong Zhang1( )Leimin Wang2
College of Mathematics and statistics, South-Central Minzu University, Wuhan 430074, China
School of Automation, China University of Geosciences, Wuhan 430074, China
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Abstract

We focused on the quasi-projective synchronization (QPS) and finite-time synchronization (FNTS) for a class of fractional-order memristive complex-valued delay neural networks (FOMCVDNNs). Rather than decomposing the complex-valued system into its real and imaginary components, we adopted a more streamlined approach by introducing a lemma associated with the complex-valued sign function. This innovative technique enabled us to design a simpler discontinuous controller. Then, based on the finite-time Lemma, measurable selection theorem, Lyapunov function theory, properties of the Mittag-Leffler function, and the fractional-order Razumikhin theorem, various substantial results were derived using a novel hybrid control scheme. In conclusion, we presented numerical simulations to illustrate the practical effectiveness of our theoretical findings.

CLC number: 34A08, 34D06, 34K37, 93C23

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AIMS Mathematics
Pages 7627-7644

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Cite this article:
Zhu J, Zhang G, Wang L. Quasi-projective and finite-time synchronization of fractional-order memristive complex-valued delay neural networks via hybrid control. AIMS Mathematics, 2024, 9(3): 7627-7644. https://doi.org/10.3934/math.2024370

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Received: 29 December 2023
Revised: 29 January 2024
Accepted: 04 February 2024
Published: 15 March 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)