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dc.contributor.authorYagle, Andrew E.en_US
dc.date.accessioned2006-12-19T19:14:55Z
dc.date.available2006-12-19T19:14:55Z
dc.date.issued2000-10-01en_US
dc.identifier.citationYagle, 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.issn0266-5611en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/49105
dc.description.abstractWe 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.extent3118 bytes
dc.format.extent128149 bytes
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherIOP Publishing Ltden_US
dc.titleDiscrete layer-stripping algorithms and feasibility conditions for the 2D inverse conductivity problemen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPhysicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI 48109-2122, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/49105/2/ip0504.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1088/0266-5611/16/5/304en_US
dc.identifier.sourceInverse Problems.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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