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Research Article | Open Access

Prescribed-time synchronization of inertial memristive neural networks with time-varying delays

Yi Zhu1,2, Minghui Jiang1,2( )
Three Gorges Mathematical Research Center, China Three Gorges University, Yichang 443002, Hubei, China
College of Science, China Three Gorges University, Yichang 443002, Hubei, China
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Abstract

This study focused on the prescribed-time synchronization of inertial memristive neural networks (IMNNs) with time-varying delays. Based on existing prescribed-time control theory, a prescribed-time feedback controller suitable for IMNNs was designed by means of a time-varying scaling function. Moreover, the sufficient criteria for the prescribed-time synchronization (PTS) of IMNNs was derived using the non-reduced order method and the prescribed-time stability lemma. The effectiveness of our theoretical results was conclusively demonstrated through a numerical simulation.

Keywords

prescribed-time synchronizationinertial memristive neural networkstime-varying delaynon-reduced order method
CLC number: 34K35, 92B20, 93D40

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AIMS Mathematics
Volume 10 Issue 4,
April 2025
Pages 9900-9916
DOI: 10.3934/math.2025453

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Cite this article:
Zhu Y, Jiang M. Prescribed-time synchronization of inertial memristive neural networks with time-varying delays. AIMS Mathematics, 2025, 10(4): 9900-9916. https://doi.org/10.3934/math.2025453

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Received: 03 March 2025
Revised: 16 April 2025
Accepted: 18 April 2025
Published: 15 April 2025
©2025 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)