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Research Article | Open Access

Synchronization analysis of delayed quaternion-valued memristor-based neural networks by a direct analytical approach

Jun Guo1,2( )Yanchao Shi3Shengye Wang3
College of Applied Mathematics, Chengdu University of Information Technology, Chengdu 610225, China
Key Laboratory of Numerical Simulation of Sichuan Provincial Universities, School of Mathematics and Information Sciences, Neijiang Normal Univeristy, Neijiang 641000, China
School of Sciences, Southwest Petroleum University, Chengdu 610500, China
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Abstract

This issue discusses the asymptotic synchronization and the exponential synchronization for memristor-based quaternion-valued neural networks under the time-varying delays. Some criteria for synchronization of the memristor-based quaternion-valued neural networks are given by exploiting the set-valued theory, the differential inclusion theory, some analytic techniques, as well as constructing novel controllers, It is worth noting that the synchronization problem about the memristor-based quaternion-valued neural networks were studied by the direct analysis method in this paper. Finally, the main theoretical results were verified by numerical simulations.

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Electronic Research Archive
Pages 3377-3395

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Cite this article:
Guo J, Shi Y, Wang S. Synchronization analysis of delayed quaternion-valued memristor-based neural networks by a direct analytical approach. Electronic Research Archive, 2024, 32(5): 3377-3395. https://doi.org/10.3934/era.2024156

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Received: 11 January 2024
Revised: 12 March 2024
Accepted: 22 April 2024
Published: 15 May 2024
©2024 the Author(s), licensee AIMS Press.

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