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Blind deconvolution of sources from the transmission responses of one-dimensional inhomogeneous continuous and discrete layered absorbing media

dc.contributor.authorYagle, Andrew E.en_US
dc.date.accessioned2006-12-19T19:14:41Z
dc.date.available2006-12-19T19:14:41Z
dc.date.issued1997-08-01en_US
dc.identifier.citationYagle, Andrew E (1997). "Blind deconvolution of sources from the transmission responses of one-dimensional inhomogeneous continuous and discrete layered absorbing media ." Inverse Problems. 13(4): 1137-1151. <http://hdl.handle.net/2027.42/49102>en_US
dc.identifier.issn0266-5611en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/49102
dc.description.abstractNon-destructive testing and reconstruction of lossy non-uniform transmission lines require solving inverse scattering problems for inhomogeneous one-dimensional (1D) lossy media. Often the source waveform used to probe the medium is unknown, since it cannot be measured separately. This paper shows that the blind deconvolution problem of reconstructing both an unknown source and an unknown lossy 1D medium can be solved, provided the medium absorption is sufficiently large. We generalize the minimum-phase property of the transmission response to a more severe property for lossy media. We also show how partial knowledge of the source can be used to reconstruct low-loss and lossless 1D media. Both discrete and continuous 1D layered media are considered. Numerical examples are presented.en_US
dc.format.extent3118 bytes
dc.format.extent209547 bytes
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherIOP Publishing Ltden_US
dc.titleBlind deconvolution of sources from the transmission responses of one-dimensional inhomogeneous continuous and discrete layered absorbing mediaen_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/2027.42/49102/2/ip7417.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1088/0266-5611/13/4/017en_US
dc.identifier.sourceInverse Problems.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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