First- and second-order hypothesis testing for mixed memoryless sources with general mixture

Te Sun Han, Ryo Nomura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The first- and second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to ϵ, is called the ϵ-optimum exponent. In this paper, we first give the second-order ϵ-exponent in the case where the null hypothesis and the alternative hypothesis are a mixed memoryless source and a stationary memoryless source, respectively. We next generalize this setting to the case where the alternative hypothesis is also a mixed memoryless source. We address the first-order ϵ-optimum exponent in this setting.

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Information Theory, ISIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-130
Number of pages5
ISBN (Electronic)9781509040964
DOIs
Publication statusPublished - 2017 Aug 9
Externally publishedYes
Event2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany
Duration: 2017 Jun 252017 Jun 30

Publication series

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

Other

Other2017 IEEE International Symposium on Information Theory, ISIT 2017
CountryGermany
CityAachen
Period17/6/2517/6/30

Fingerprint

Hypothesis Testing
Exponent
First-order
Testing
Error Probability
Type II error
Type I error
Alternatives
Null hypothesis
Error probability
Generalise

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

Cite this

Han, T. S., & Nomura, R. (2017). First- and second-order hypothesis testing for mixed memoryless sources with general mixture. In 2017 IEEE International Symposium on Information Theory, ISIT 2017 (pp. 126-130). [8006503] (IEEE International Symposium on Information Theory - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2017.8006503

First- and second-order hypothesis testing for mixed memoryless sources with general mixture. / Han, Te Sun; Nomura, Ryo.

2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 126-130 8006503 (IEEE International Symposium on Information Theory - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Han, TS & Nomura, R 2017, First- and second-order hypothesis testing for mixed memoryless sources with general mixture. in 2017 IEEE International Symposium on Information Theory, ISIT 2017., 8006503, IEEE International Symposium on Information Theory - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 126-130, 2017 IEEE International Symposium on Information Theory, ISIT 2017, Aachen, Germany, 17/6/25. https://doi.org/10.1109/ISIT.2017.8006503
Han TS, Nomura R. First- and second-order hypothesis testing for mixed memoryless sources with general mixture. In 2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 126-130. 8006503. (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2017.8006503
Han, Te Sun ; Nomura, Ryo. / First- and second-order hypothesis testing for mixed memoryless sources with general mixture. 2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 126-130 (IEEE International Symposium on Information Theory - Proceedings).
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