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dc.contributor.advisorArıkan, Orhanen_US
dc.contributor.authorÖzdemir, Ahmet Kemalen_US
dc.date.accessioned2016-01-08T20:16:00Z
dc.date.available2016-01-08T20:16:00Z
dc.date.issued1998
dc.identifier.urihttp://hdl.handle.net/11693/18073
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1998.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1998.en_US
dc.descriptionIncludes bibliographical references leaves 43-45.en_US
dc.description.abstractRecently blind identification of single-input multiple-output (SIMO) FIR channels has received considerable attention. The obtained exact identification approaches place over-restrictive constraints on the channels. In this thesis least set of constraints on the channels are placed and the noise-free blind channel identification problem is solved in two stages: The identification of the uncommon zeros followed by the identification of the common zeros of the channels. The minimum number of samples required to identify the uncommon zeros is specified, and closed form solutions are obtained. Also a binary-tree algorithm is proposed for the computation of the uncommon zeros efficiently. Then the common zeros of the channels are identified by a novel pruning algorithm. Finally a simulation example is presented to illustrate these ideas.en_US
dc.description.statementofresponsibilityÖzdemir, Ahmet Kemalen_US
dc.format.extentix, 55 leavesen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBlind channel identificationen_US
dc.subjectBlind deconvolutionen_US
dc.subjectSystem identificationen_US
dc.subjectFractional samplingen_US
dc.subject.lccTK5102.5 .O93 1998en_US
dc.subject.lcshSystem identification.en_US
dc.titleExact blind channel estimatoren_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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