Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/112114
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Applied Mathematics-
dc.creatorCen, S-
dc.creatorShin, K-
dc.creatorZhou, Z-
dc.date.accessioned2025-03-27T03:14:38Z-
dc.date.available2025-03-27T03:14:38Z-
dc.identifier.issn0749-159X-
dc.identifier.urihttp://hdl.handle.net/10397/112114-
dc.language.isoenen_US
dc.publisherJohn Wiley & Sons, Inc.en_US
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.en_US
dc.rights© 2024 The Author(s). Numerical Methods for Partial Differential Equations published by Wiley Periodicals LLC.en_US
dc.rightsThe following publication S. Cen, K. Shin and Z. Zhou, Determining a time-varying potential in time-fractional diffusion from observation at a single point, Numer. Methods Partial Differ. Eq. 40 (2024), e23136 is available at https://doi.org/10.1002/num.23136.en_US
dc.subjectError analysisen_US
dc.subjectInverse potential problemen_US
dc.subjectLipschitz stabilityen_US
dc.subjectNumerical recoveryen_US
dc.subjectTime-fractional diffusionen_US
dc.titleDetermining a time-varying potential in time-fractional diffusion from observation at a single pointen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume40-
dc.identifier.issue6-
dc.identifier.doi10.1002/num.23136-
dcterms.abstractWe discuss the identification of a time-dependent potential in a time-fractional diffusion model from a boundary measurement taken at a single point. Theoretically, we establish a conditional Lipschitz stability for this inverse problem. Numerically, we develop an easily implementable iterative algorithm to recover the unknown coefficient, and also derive rigorous error bounds for the discrete reconstruction. These results are attained by leveraging the (discrete) solution theory of direct problems, and applying error estimates that are optimal with respect to problem data regularity. Numerical simulations are provided to demonstrate the theoretical results.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationNumerical methods for partial differential equations, Nov. 2024, v. 40, no. 6, e23136-
dcterms.isPartOfNumerical methods for partial differential equations-
dcterms.issued2024-11-
dc.identifier.scopus2-s2.0-85200488740-
dc.identifier.eissn1098-2426-
dc.identifier.artne23136-
dc.description.validate202503 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Research Foundation of Koreaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Cen_Determining_Time‐varying_Potential.pdf2.18 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

2
Citations as of Apr 1, 2025

Downloads

3
Citations as of Apr 1, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.