Vazquez-Vilar, GonzaloTauste Campo, Adrià, 1982-Guillén i Fábregas, A. (Albert)Martínez, Alfonso, 1973-2018-12-052018-12-052016Vazquez-Vilar G, Tauste A, Guillén A, Martinez A. Bayesian M-Ary hypothesis testing: the meta-converse and Verdú-Han bounds are tight. IEEE Trans Inf Theory. 2016;62(5):2324 - 33. DOI: 10.1109/TIT.2016.25420800018-9448http://hdl.handle.net/10230/36000Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesis testing are derived. The first expression corresponds to the error probability of an induced binary hypothesis test and implies the tightness of the meta-converse bound by Polyanskiy et al.; the second expression is a function of an information-spectrum measure and implies the tightness of a generalized Verdú-Han lower bound. The formulas characterize the minimum error probability of several problems in information theory and help to identify the steps where existing converse bounds are loose.application/pdfeng© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at http://dx.doi.org/10.1109/TIT.2016.2542080info:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TIT.2016.2542080Error probabilityTestingBayes methodsRandom variablesChannel codingElectronic mailinfo:eu-repo/semantics/openAccess