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Research Article | Open Access

Novel fixed-time synchronization results of fractional-order fuzzy cellular neural networks with delays and interactions

Jun Liu1,2Wenjing Deng1Shuqin Sun3( )Kaibo Shi4
School of Mathematics Sciences, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
Visual Computing and Virtual Reality Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, Sichuan 610068, China
School of Mathematics Education, China West Normal University, Nanchong Sichuan 637002, China
School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan 610106, China
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Abstract

This research investigated the fixed-time (FXT) synchronization of fractional-order fuzzy cellular neural networks (FCNNs) with delays and interactions based on an enhanced FXT stability theorem. By conceiving proper Lyapunov functions and applying inequality techniques, several sufficient conditions were obtained to vouch for the fixed-time synchronization (FXTS) of the discussed systems through two categories of control schemes. Moreover, in terms of another FXT stability theorem, different upper-bounding estimating formulas for settling time (ST) were given, and the distinctions between them were pointed out. Two examples were delivered at length to demonstrate the conclusions.

CLC number: 37N35, 93D15, 93D21, 93D40

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AIMS Mathematics
Pages 13245-13264

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Cite this article:
Liu J, Deng W, Sun S, et al. Novel fixed-time synchronization results of fractional-order fuzzy cellular neural networks with delays and interactions. AIMS Mathematics, 2024, 9(5): 13245-13264. https://doi.org/10.3934/math.2024646

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Received: 18 February 2024
Revised: 26 March 2024
Accepted: 07 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 (https://creativecommons.org/licenses/by/4.0)