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dc.contributor.authorJensen, Bjørn
dc.contributor.authorKnudsen, Kim
dc.contributor.authorSchlüter, Hjørdis
dc.date.accessioned2024-02-21T12:34:15Z
dc.date.available2024-02-21T12:34:15Z
dc.date.issued2023
dc.identifier.citationJensen, B., Knudsen, K., & Schlüter, H. (2023). Conductivity reconstruction from power density data in limited view. <i>Mathematica Scandinavica</i>, <i>129</i>(1), 140-160. <a href="https://doi.org/10.7146/math.scand.a-135820" target="_blank">https://doi.org/10.7146/math.scand.a-135820</a>
dc.identifier.otherCONVID_183978093
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/93553
dc.description.abstractIn acousto-electric tomography, the objective is to extract information about the interior electrical conductivity in a physical body from knowledge of the interior power density data generated from prescribed boundary conditions for the governing elliptic partial differential equation. In this note, we consider the problem when the controlled boundary conditions are applied only on a small subset of the full boundary. We demonstrate using the unique continuation principle that the Runge approximation property is valid also for this special case of limited view data. As a consequence, we guarantee the existence of finitely many boundary conditions such that the corresponding solutions locally satisfy a non-vanishing gradient condition. This condition is essential for conductivity reconstruction from power density data. In addition, we adapt an existing reconstruction method intended for the full data situation to our setting. We implement the method numerically and investigate the opportunities and shortcomings when reconstructing from two fixed boundary conditions.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherRoyal Danish Library
dc.relation.ispartofseriesMathematica Scandinavica
dc.rightsIn Copyright
dc.titleConductivity reconstruction from power density data in limited view
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202402212020
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange140-160
dc.relation.issn0025-5521
dc.relation.numberinseries1
dc.relation.volume129
dc.type.versionacceptedVersion
dc.rights.copyright© Royal Danish Library 2023
dc.rights.accesslevelopenAccessfi
dc.subject.ysotomografia
dc.subject.ysoosittaisdifferentiaaliyhtälöt
dc.subject.ysonumeerinen analyysi
dc.subject.ysoinversio-ongelmat
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p17798
jyx.subject.urihttp://www.yso.fi/onto/yso/p12392
jyx.subject.urihttp://www.yso.fi/onto/yso/p15833
jyx.subject.urihttp://www.yso.fi/onto/yso/p27912
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.7146/math.scand.a-135820
jyx.fundinginformationBJ was supported by the Academy of Finland (grant no. 320022).
dc.type.okmA1


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