Discrete layer-stripping algorithms and feasibility conditions for the 2D inverse conductivity problem

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dc.contributor.author Yagle, Andrew E. en_US
dc.date.accessioned 2006-12-19T19:14:55Z
dc.date.available 2006-12-19T19:14:55Z
dc.date.issued 2000-10-01 en_US
dc.identifier.citation Yagle, Andrew E (2000). "Discrete layer-stripping algorithms and feasibility conditions for the 2D inverse conductivity problem." Inverse Problems. 16(5): 1157-1171. <http://hdl.handle.net/2027.42/49105> en_US
dc.identifier.issn 0266-5611 en_US
dc.identifier.uri http://hdl.handle.net/2027.42/49105
dc.description.abstract We develop a discrete layer-stripping algorithm for the 2D inverse conductivity problem. Unlike previous algorithms, this algorithm transforms the problem into a time-varying 1D Schrödinger equation inverse scattering problem, discretizes this problem and then solves the discrete problem exactly. This approach has three advantages: (i) the poor conditioning inherent in the problem is concentrated in the solution of a linear integral transform at the beginning of the problem, to which standard regularization techniques may be applied and (ii) feasibility conditions on the transformed data are obtained, satisfaction of which ensures that (iii) the solution of the discrete nonlinear inverse scattering problem is exact and stable. Other contributions include solution of discrete Schrödinger equation inverse potential problems with time-varying potentials by both layer-stripping algorithms and solution of nested systems of equations which amount to a time-varying discrete version of the Gel'fand-Levitan equation. An analytic and numerical example is supplied to demonstrate the operation of the algorithm. en_US
dc.format.extent 3118 bytes
dc.format.extent 128149 bytes
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher IOP Publishing Ltd en_US
dc.title Discrete layer-stripping algorithms and feasibility conditions for the 2D inverse conductivity problem en_US
dc.type Article en_US
dc.subject.hlbsecondlevel Physics en_US
dc.subject.hlbtoplevel Science en_US
dc.description.peerreviewed Peer Reviewed en_US
dc.contributor.affiliationum Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI 48109-2122, USA en_US
dc.contributor.affiliationumcampus Ann Arbor en_US
dc.description.bitstreamurl http://deepblue.lib.umich.edu/bitstream/2027.42/49105/2/ip0504.pdf en_US
dc.identifier.doi http://dx.doi.org/10.1088/0266-5611/16/5/304 en_US
dc.identifier.source Inverse Problems. en_US
dc.owningcollname Interdisciplinary and Peer-Reviewed
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