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Generation of random bits from Poisson processes

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dc.contributor.authorPae, Sung-il-
dc.date.available2020-07-10T04:40:32Z-
dc.date.created2020-07-06-
dc.date.issued2018-
dc.identifier.issn1064-1246-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/4750-
dc.description.abstractIn a recent work, Bernardini and Rinaldo generalize and attempt to improve upon Elias method to obtain unbiased random bits from a geometric distribution resulted from a Poisson process. As a response, we analyse the output rates of their method and compare with the original binary Elias method applied on a Bernoulli process resulted from the same Poisson process, which turns out to be much simpler to implement and to have a higher output rate.-
dc.language영어-
dc.language.isoen-
dc.publisherIOS PRESS-
dc.subjectEFFICIENT CONSTRUCTION-
dc.titleGeneration of random bits from Poisson processes-
dc.typeArticle-
dc.contributor.affiliatedAuthorPae, Sung-il-
dc.identifier.doi10.3233/JIFS-169835-
dc.identifier.scopusid2-s2.0-85059469911-
dc.identifier.wosid000459214900014-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT & FUZZY SYSTEMS, v.35, no.6, pp.5939 - 5946-
dc.relation.isPartOfJOURNAL OF INTELLIGENT & FUZZY SYSTEMS-
dc.citation.titleJOURNAL OF INTELLIGENT & FUZZY SYSTEMS-
dc.citation.volume35-
dc.citation.number6-
dc.citation.startPage5939-
dc.citation.endPage5946-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusEFFICIENT CONSTRUCTION-
dc.subject.keywordAuthorrandom bits-
dc.subject.keywordAuthorPoisson process-
dc.subject.keywordAuthorBernoulli process-
dc.subject.keywordAuthorgeometric distribution-
dc.subject.keywordAuthorElias algorithm-
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