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Research Article | Open Access

Finite-time synchronization for fractional-order delayed quaternion valued neural networks by using the negative definition of matrix

Zhimin Wan1( )Zhengqiu Zhang2( )Zhenbo Cheng1
Clinical Laboratory of Hunnan Provincial People' s Hospital, The First Hospital of Hunan Normal University, Changsha, 410000, China
College of Mathematics, Hunan University, Changsha, 410006, China
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Abstract

In the study, the finite-time synchronization (FTSN) for a kind of master-slave quaternion-valued fractional-order neural networks (MSQVFONNS) is discussed. By using the negative definition of matrix and the properties of the determinant, two novel criteria on the FTSN for the considered MSFOQVNNS are established. The negative definition of the matrix and the properties of the determinant are introduced to study the FTSN for neural networks (NNs) in our article. Since until, studies about the FTSN for the NNs are rare and researchers have only used the linear matrix inequality (LMI), finite time stability theorems (FTSTs) of fractional order and Lyapunov direct method to study the FTSN for the MSFOQVNNS, so far, our method to study the FTSN for the MSFOQVNNS is of definite significance.

CLC number: 34K24

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AIMS Mathematics
Pages 7791-7820

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Cite this article:
Wan Z, Zhang Z, Cheng Z. Finite-time synchronization for fractional-order delayed quaternion valued neural networks by using the negative definition of matrix. AIMS Mathematics, 2026, 11(3): 7791-7820. https://doi.org/10.3934/math.2026321

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Received: 06 December 2025
Revised: 02 March 2026
Accepted: 03 March 2026
Published: 15 March 2026
©2026 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)