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Research Article | Open Access

Fixed-time control of switched memristor-based BAM neural networks with time-varying delays

Ziqing Yuan1( ), Zuowei Cai2
Department of Applied Mathematics, Huaihua University, Huaihua 418000, China
College of Information Science and Engineering, Hunan Women's University, Changsha 410002, China
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Abstract

This study investigates the prespecified-/finite-time stability for a class of memristor-based BAM neural networks (MBAMNNs) with discontinuity. By C-regular Lyapunov approach stability theories, some criteria are established to ensure that the switched MBAMNNs can achieve prespecified-/finite-time stabilization, which are independent of the initial states. Finally, some numerical examples demonstrate the effectiveness of the proposed criteria. This work provides a theoretical foundation for precise temporal control in complex neural networks.

Keywords

BAM neural networksprespecified-time stabilityfinite-time stabilityexternal input controller

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Electronic Research Archive
Volume 33 Issue 11,
November 2025
Pages 6922-6951
DOI: 10.3934/era.2025305

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Cite this article:
Yuan Z, Cai Z. Fixed-time control of switched memristor-based BAM neural networks with time-varying delays. Electronic Research Archive, 2025, 33(11): 6922-6951. https://doi.org/10.3934/era.2025305

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Received: 14 September 2025
Revised: 31 October 2025
Accepted: 11 November 2025
Published: 17 November 2025
©2025 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)