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Research Article | Open Access

Accelerating the convergence of a two-dimensional periodic nonuniform sampling series through the incorporation of a bivariate Gaussian multiplier

Rashad M. Asharabi( ), Somaia M. Alhazmi
Department of Mathematics, College of Arts and Sciences, Najran University, Najran 66462, Saudi Arabia
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Abstract

Recently, in the field of periodic nonuniform sampling, researchers (Wang et al., 2019; Asharabi, 2023) have investigated the incorporation of a Gaussian multiplier in the one-dimensional series to improve its convergence rate. Building on these developments, this paper aimed to accelerate the convergence of the two-dimensional periodic nonuniform sampling series by incorporating a bivariate Gaussian multiplier. This approach utilized a complex-analytic technique and is applicable to a wide range of functions. Specifically, it applies to the class of bivariate entire functions of exponential type that satisfy a decay condition, as well as to the class of bivariate analytic functions defined on a bivariate horizontal strip. The original convergence rate of the two-dimensional periodic nonuniform sampling is given by O(N−p), where p≥1. However, through the implementation of this acceleration technique, the convergence rate improved drastically and followed an exponential order, specifically e−αN, where α>0. To validate the theoretical analysis presented, the paper conducted rigorous numerical experiments.

CLC number: 30E10, 30D10, 30D15, 41A25, 41A80, 65B10, 65D05, 94A20

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AIMS Mathematics
Pages 30898-30921

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Cite this article:
Asharabi RM, Alhazmi SM. Accelerating the convergence of a two-dimensional periodic nonuniform sampling series through the incorporation of a bivariate Gaussian multiplier. AIMS Mathematics, 2024, 9(11): 30898-30921. https://doi.org/10.3934/math.20241491

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Received: 30 June 2024
Revised: 29 September 2024
Accepted: 22 October 2024
Published: 30 October 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)