A data-driven model reduction approach for backward fractional diffusion-wave equations

Fuente: arXiv
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Autori principali: Cen, Dakang, Li, Zhiyuan, Zhang, Wenlong
Natura: Preprint
Pubblicazione: 2026
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author Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
author_facet Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
contents In this work, we propose an observation system based on the available data which solution is one-be-one mapping to the forward problem(with the unknown initial function) solution. It implies their solutions share the same linear structure in the finite dimensional space. Theoretical results show model reduction approaches constructed for the observation system also work well for the forward problem, which significantly improve the efficiency of solving the inverse problem. Several numerical examples are presented to support our finding.
format Preprint
id arxiv_https___arxiv_org_abs_2604_22211
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A data-driven model reduction approach for backward fractional diffusion-wave equations
Cen, Dakang
Li, Zhiyuan
Zhang, Wenlong
Numerical Analysis
35R11, 35R09, 35B40
In this work, we propose an observation system based on the available data which solution is one-be-one mapping to the forward problem(with the unknown initial function) solution. It implies their solutions share the same linear structure in the finite dimensional space. Theoretical results show model reduction approaches constructed for the observation system also work well for the forward problem, which significantly improve the efficiency of solving the inverse problem. Several numerical examples are presented to support our finding.
title A data-driven model reduction approach for backward fractional diffusion-wave equations
topic Numerical Analysis
35R11, 35R09, 35B40
url https://arxiv.org/abs/2604.22211