Afser, HuseyinYildirim, Ugur2025-01-062025-01-062020978-1-7281-7206-42165-0608https://hdl.handle.net/20.500.14669/192628th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORKWe 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.trinfo:eu-repo/semantics/closedAccessBayesian Hyptohesis TestingRobust Hyptohesis TestingMethod of TypesChernoff DistanceConference ObjectWOS:000653136100275N/A