Bayesian M-Ary hypothesis testing: the meta-converse and Verdú-Han bounds are tight
Bayesian M-Ary hypothesis testing: the meta-converse and Verdú-Han bounds are tight
Citació
- Vazquez-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.2016.2542080
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Descripció
Resum
Two 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.