Deconvolution using projections onto the epigraph set of a convex cost function

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage1641en_US
dc.citation.spage1638en_US
dc.contributor.authorTofighi, Mohammaden_US
dc.contributor.authorBozkurt, Alicanen_US
dc.contributor.authorKöse, K.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialTrabzon, Turkeyen_US
dc.date.accessioned2016-02-08T11:46:21Z
dc.date.available2016-02-08T11:46:21Z
dc.date.issued2014en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 23-25 April 2014en_US
dc.descriptionConference Name: 22nd Signal Processing and Communications Applications Conference, SIU 2014en_US
dc.description.abstractA new deconvolution algorithm based on making orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization problem is lifted by one and sets corresponding to the cost function and observations are defined. If the utilized cost function is convex in RN, the corresponding epigraph set is also convex in RN+1. The deconvolution algorithm starts with an arbitrary initial estimate in RN+1. At each iteration cycle of the algorithm, first deconvolution projections are performed onto the hyperplanes representing observations, then an orthogonal projection is performed onto epigraph of the cost function. The method provides globally optimal solutions for total variation, l1, l2, and entropic cost functions.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:46:21Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2014en
dc.identifier.doi10.1109/SIU.2014.6830560en_US
dc.identifier.urihttp://hdl.handle.net/11693/27163
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2014.6830560en_US
dc.source.titleProceedings of the 22nd Signal Processing and Communications Applications Conference, SIU 2014en_US
dc.subjectEpigraph of a cost functionen_US
dc.subjectCost functionsen_US
dc.subjectDeconvolutionen_US
dc.subjectIterative methodsen_US
dc.subjectSignal processingen_US
dc.subjectConvex cost functionen_US
dc.subjectDeconvolution algorithmen_US
dc.subjectInitial estimateen_US
dc.subjectMinimization problemsen_US
dc.subjectOptimal solutionsen_US
dc.subjectOrthogonal projectionen_US
dc.subjectProjection onto convex setsen_US
dc.subjectTotal variationen_US
dc.subjectAlgorithmsen_US
dc.titleDeconvolution using projections onto the epigraph set of a convex cost functionen_US
dc.title.alternativeDışbükey maliyet fonksiyonlaının epigraf kümesine dikey izdüşüm kullanan ters evrişim algoritmasıen_US
dc.typeConference Paperen_US

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Deconvolution using projections onto the epigraph set of a convex cost function [Dişbükey maliyet fonksiyonlarinin epigraf kümesine dikey izdüşüm kullanan ters evrişim algoritmasi].pdf
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