Bayesian Binary Hypothesis Testing Under Model Uncertainty

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dc.contributor.authorAfser, Huseyin
dc.contributor.authorYildirim, Ugur
dc.date.accessioned2025-01-06T17:36:39Z
dc.date.available2025-01-06T17:36:39Z
dc.date.issued2020
dc.description28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORK
dc.description.abstractWe consider Bayesian binary hypothesis testing problem when there is only partial knowledge about one of the distributions, while the other distribution is fully known. Specifically, let P-1 and P-2 be the distributions under two hypothesis, where P-2 is known and P-1 is unknown. We propose a test and show that if the Chernoff distance between P-1 and P-2 is known to be larger than Phi, an error exponent Phi,- epsilon, epsilon > 0, can be achieved in the Bayesian setting. If the Chernoff distance between P-1 and P-2 is not known, but another distribution Q(1) known such that l(1) distance between P-1 and Q(1) is known the smaller than a, then the same test can be applied, and it coincides with the robust hypothesis testing methods existing in the literature.
dc.description.sponsorshipIstanbul Medipol Univ
dc.identifier.isbn978-1-7281-7206-4
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1926
dc.identifier.wosWOS:000653136100275
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2020 28th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectBayesian Hyptohesis Testing
dc.subjectRobust Hyptohesis Testing
dc.subjectMethod of Types
dc.subjectChernoff Distance
dc.titleBayesian Binary Hypothesis Testing Under Model Uncertainty
dc.typeConference Object

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