The Asymptotic Generalized Poor-Verdú Bound Achieves the BSC Error Exponent at Zero Rate

Ling Hua Chang, Po Ning Chen, Fady Alajaji, Yunghsiang S. Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The generalized Poor-Verdú error lower bound for multihypothesis testing is revisited. Its asymptotic expression is established in closed-form as its tilting parameter grows to infinity. It is also shown that the asymptotic generalized bound achieves the error exponent (or reliability function) of the memoryless binary symmetric channel at zero coding rates.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2131-2136
Number of pages6
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: 21 Jul 202026 Jul 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
CountryUnited States
CityLos Angeles
Period21/07/2026/07/20

Keywords

  • Binary symmetric channel
  • error exponent
  • error probability bounds
  • hypothesis testing
  • zero coding rates

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