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Research Article | Open Access

Generalized fractional derivatives and fourier transforms in tempered distributions with applications

Amin Benaissa Cherif1Fatima Zohra Ladrani2Dalal Alhwikem3( )Ahmed Hammoudi4Khaled Zennir3Keltoum Bouhali3
Department of Mathematics, Faculty of Mathematics and Informatics, University of Science and Technology of Oran Mohamed-Boudiaf (USTOMB), El Mnaouar, BP 1505, Bir El Djir, Oran 31000, Algeria
Department of Exact Sciences, Oran Higher Training Teacher's School (ENSO), Oran, Algeria
Department of Mathematics, College of science, Qassim University, Saudi Arabia
Department of Mathematics and Informatics, Faculty of Science and Technology, University Ain Temouchent Belhadj Bouchaib, BP 284, Ain Temouchent 46000, Algeria
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Abstract

The purpose of this paper is to define and prove that the Riemann–Liouville and Caputo fractional derivatives can be computed for tempered distributions, such that the fractional derivative of a tempered distribution remains a tempered distribution. The fact that the Fourier transform operator is an isomorphism in the dual of the Schwartz space is used, and we found that the fractional Riemann–Liouville and Caputo derivatives can be written as a Fourier transform composition and inverse. In this way, we are able to generalize both fractional Riemann–Liouville and Caputo derivatives for the tempered distributions. Moreover, certain examples of fractional derivatives for some tempered distributions are provided, such as the distribution of Dirac, the distribution of Heaviside, and the distribution of principal value.

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Networks and Heterogeneous Media
Pages 868-884

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Cite this article:
Cherif AB, Ladrani FZ, Alhwikem D, et al. Generalized fractional derivatives and fourier transforms in tempered distributions with applications. Networks and Heterogeneous Media, 2025, 20(3): 868-884. https://doi.org/10.3934/nhm.2025037

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Received: 07 April 2025
Revised: 29 May 2025
Accepted: 05 June 2025
Published: 18 July 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)