Intrinsic Randomness Problem with Respect to a Subclass of f-divergence

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1 Citation (Scopus)

Abstract

This paper deals with the intrinsic randomness (IR) problem, which is one of typical random number generation problems. In the literature, the optimum achievable rates in the IR problem with respect to the variational distance as well as the Kullback-Leibler (KL) divergence have already been analyzed. On the other hand, in this study we consider the IR problem with respect to a subclass of f-divergences. The f-divergence is a general non-negative measure between two probabilistic distributions and includes several important measures such as the total variational distance, the χ2-divergence, the KL divergence, and so on. Hence, it is meaningful to consider the IR problem with respect to the f-divergence. In this paper, we assume some conditions on the f-divergence for simplifying the analysis. That is, we focus on a subclass of f-divergences. In this problem setting, we first derive the general formula of the optimum achievable rate. Next, we show that it is easy to derive the optimum achievable rate with respect to the variational distance, the KL divergence, and the Hellinger distance from our general formula.

Original languageEnglish
Title of host publication2019 IEEE Information Theory Workshop, ITW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538669006
DOIs
Publication statusPublished - 2019 Aug
Event2019 IEEE Information Theory Workshop, ITW 2019 - Visby, Sweden
Duration: 2019 Aug 252019 Aug 28

Publication series

Name2019 IEEE Information Theory Workshop, ITW 2019

Conference

Conference2019 IEEE Information Theory Workshop, ITW 2019
CountrySweden
CityVisby
Period19/8/2519/8/28

ASJC Scopus subject areas

  • Software
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Nomura, R. (2019). Intrinsic Randomness Problem with Respect to a Subclass of f-divergence. In 2019 IEEE Information Theory Workshop, ITW 2019 [8989245] (2019 IEEE Information Theory Workshop, ITW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITW44776.2019.8989245