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Monotonicity of step sizes of MSE-Optimal symmetric uniform scalar quantizers
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dc.contributor.authorNa, Sangsin-
dc.contributor.authorNeuhoff, David L.-
dc.date.issued2019-03-01-
dc.identifier.issn0018-9448-
dc.identifier.urihttps://dspace.ajou.ac.kr/dev/handle/2018.oak/30346-
dc.description.abstractFor generalized gamma probability densities, this paper studies the monotonicity of step sizes of optimal symmetric uniform scalar quantizers with respect to mean squared-error distortion. The principal results are that for the special cases of Gaussian, Laplacian, two-sided Rayleigh, and gamma densities, optimal step size monotonically decreases when the number of levels N increases by two, and that for any generalized gamma density and all sufficiently large N, optimal step size again decreases when N increases by two. Also, it is shown that for a Laplacian density and sufficiently large N, optimal step size decreases when N increases by just one.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.subject.meshGeneralized Gamma-
dc.subject.meshIndexes-
dc.subject.meshMonotonicity-
dc.subject.meshOptimal step size-
dc.subject.meshUniform quantization-
dc.titleMonotonicity of step sizes of MSE-Optimal symmetric uniform scalar quantizers-
dc.typeArticle-
dc.citation.endPage1792-
dc.citation.startPage1782-
dc.citation.titleIEEE Transactions on Information Theory-
dc.citation.volume65-
dc.identifier.bibliographicCitationIEEE Transactions on Information Theory, Vol.65, pp.1782-1792-
dc.identifier.doi10.1109/tit.2018.2867182-
dc.identifier.scopusid2-s2.0-85052695194-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=18-
dc.subject.keywordgeneralized gamma densities-
dc.subject.keywordMonotonicity-
dc.subject.keywordMSE distortion-
dc.subject.keywordoptimal step size-
dc.subject.keywordsymmetric uniform quantization-
dc.description.isoafalse-
dc.subject.subareaInformation Systems-
dc.subject.subareaComputer Science Applications-
dc.subject.subareaLibrary and Information Sciences-
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