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

Ryo Nomura*

*この研究の対応する著者

研究成果

2 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2019 IEEE Information Theory Workshop, ITW 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538669006
DOI
出版ステータスPublished - 2019 8
イベント2019 IEEE Information Theory Workshop, ITW 2019 - Visby, Sweden
継続期間: 2019 8 252019 8 28

出版物シリーズ

名前2019 IEEE Information Theory Workshop, ITW 2019

Conference

Conference2019 IEEE Information Theory Workshop, ITW 2019
国/地域Sweden
CityVisby
Period19/8/2519/8/28

ASJC Scopus subject areas

  • ソフトウェア
  • 計算理論と計算数学
  • コンピュータ ネットワークおよび通信
  • 情報システム

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