Scattered point measurement-based regularization for backward problems for fractional wave equations

Fuente: arXiv
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Hauptverfasser: Cen, Dakang, Li, Zhiyuan, Zhang, Wenlong
Format: Preprint
Veröffentlicht: 2025
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author Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
author_facet Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
contents In this work, we are devoted to the reconstruction of an unknown initial value from the terminal data. The asymptotic and root-distribution properties of Mittag-Leffler functions are used to establish stability of the backward problem. Furthermore, we introduce a regularization method that effectively handles scattered point measurements contaminated with stochastic noise. Furthermore, we prove the stochastic convergence of our proposed regularization and provide an iterative algorithm to find the optimal regularization parameter. Finally, several numerical experiments are presented to demonstrate the efficiency and accuracy of the algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2506_17575
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scattered point measurement-based regularization for backward problems for fractional wave equations
Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
Numerical Analysis
35R11, 35R09, 35B40
In this work, we are devoted to the reconstruction of an unknown initial value from the terminal data. The asymptotic and root-distribution properties of Mittag-Leffler functions are used to establish stability of the backward problem. Furthermore, we introduce a regularization method that effectively handles scattered point measurements contaminated with stochastic noise. Furthermore, we prove the stochastic convergence of our proposed regularization and provide an iterative algorithm to find the optimal regularization parameter. Finally, several numerical experiments are presented to demonstrate the efficiency and accuracy of the algorithm.
title Scattered point measurement-based regularization for backward problems for fractional wave equations
topic Numerical Analysis
35R11, 35R09, 35B40
url https://arxiv.org/abs/2506.17575