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A numerical solution of the dynamic vector tomography problem using the truncated singular value decomposition method Full article

Journal Journal of Inverse and Ill-Posed Problems
ISSN: 0928-0219 , E-ISSN: 1569-3945
Output data Year: 2024, Volume: 32, Number: 1, DOI: 10.1515/jiip-2022-0019
Tags Dynamic vector tomography; longitudinal ray transform; orthogonal polynomial; singular value decomposition; transverse ray transform
Authors Polyakova Anna P. 1 , Svetov Ivan E. 1
Affiliations
1 Sobolev Institute of Mathematics

Funding (2)

1 Sobolev Institute of Mathematics FWNF-2022-0009
2 Russian Foundation for Basic Research 19-51-12008

Abstract: We consider a problem of dynamic 2D vector tomography, i.e. the object under investigation changes during the data acquisition. More precisely, we consider the case when the object motion is a combination of rotation and shifting. The task is then to reconstruct the searched-for vector field by known values of the dynamic ray transforms. In order to solve this dynamic inverse problem, we first study properties of the dynamic ray transforms operators. In particular, the singular value decompositions of the operators are constructed using classic orthogonal polynomials. Following from this study, a numerical algorithm for solving the dynamic problem is proposed based on the truncated singular value decomposition method.
Cite: Polyakova A.P. , Svetov I.E.
A numerical solution of the dynamic vector tomography problem using the truncated singular value decomposition method
Journal of Inverse and Ill-Posed Problems. 2024. V.32. N1. DOI: 10.1515/jiip-2022-0019 WOS Scopus РИНЦ OpenAlex
Dates:
Submitted: Mar 17, 2022
Accepted: Jul 17, 2022
Published online: Oct 25, 2022
Published print: Feb 1, 2024
Identifiers:
Web of science: WOS:000871634700001
Scopus: 2-s2.0-85141132489
Elibrary: 57963790
OpenAlex: W4307282813
Citing:
DB Citing
Web of science 2
Scopus 3
OpenAlex 3
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