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dc.contributor.advisorÖzaktaş, Haldun M.
dc.contributor.authorGülcü, Talha Cihad
dc.date.accessioned2016-01-08T18:15:27Z
dc.date.available2016-01-08T18:15:27Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/11693/15240
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2011.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2011.en_US
dc.descriptionIncludes bibliographical references leaves 81-93.en_US
dc.description.abstractIn this thesis, we study how to encode finite energy signals by finitely many bits. Since such an encoding is bound to be lossy, there is an inevitable reconstruction error in the recovery of the original signal. We also analyze this reconstruction error. In our work, we not only verify the intuition that finiteness of the energy for a signal implies finite degree of freedom, but also optimize the reconstruction parameters to get the minimum possible reconstruction error by using a given number of bits and to achieve a given reconstruction error by using minimum number of bits. This optimization leads to a number of bits vs reconstruction error curve consisting of the best achievable points, which reminds us the rate distortion curve in information theory. However, the rate distortion theorem are not concerned with sampling, whereas we need to take sampling into consideration in order to reduce the finite energy signal we deal with to finitely many variables to be quantized. Therefore, we first propose a finite sample representation scheme and question the optimality of it. Then, after representing the signal of interest by finite number of samples at the expense of a certain error, we discuss several quantization methods for these finitely many samples and compare their performances.en_US
dc.description.statementofresponsibilityGülcü, Talha Cihaden_US
dc.format.extentxii, 93 leaves, illustrationsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFinite Energy Signalsen_US
dc.subjectSamplingen_US
dc.subjectFinite Sample Representationen_US
dc.subjectDegree of Freedom (DOF)en_US
dc.subjectSpace Bandwidth Producten_US
dc.subjectReconstruction Erroren_US
dc.subjectUniform Quantizationen_US
dc.subjectVector Quantizationen_US
dc.subjectQuantization Erroren_US
dc.subjectRate Distortion Theoryen_US
dc.subject.lccTK5102.9 .G85 2011en_US
dc.subject.lcshSignal processing--Mathematics.en_US
dc.subject.lcshSampling (Statistics)en_US
dc.titleFinite representation of finite energy signalsen_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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