Bayesian Binary Hypothesis Testing under Model Uncertainty
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Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
We 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 P1 and P2 be the distributions under two hypothesis, where P2 is known and P1 is unknown. We propose a test and show that if the Chernoff distance between P1 and P2 is known to be larger than ?, an error exponent ?-?, ?>0, can be achieved in the Bayesian setting. If the Chernoff distance between P1 and P2 is not known, but another distribution Q1 known such that l1 distance between P1 and Q1 is known the smaller than ?, then the same test can be applied, and it coincides with the robust hypothesis testing methods existing in the literature. © 2020 IEEE.
Açıklama
28th Signal Processing and Communications Applications Conference, SIU 2020 -- 5 October 2020 through 7 October 2020 -- Gaziantep -- 166413
Anahtar Kelimeler
Bayesian Hyptohesis Testing, Chernoff Distance, Method of Types, Robust Hyptohesis Testing
Kaynak
2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings
