2019年
Intrinsic Randomness Problem with Respect to a Subclass of f-divergence
2019 IEEE INFORMATION THEORY WORKSHOP (ITW)
- 開始ページ
- 80
- 終了ページ
- 84
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- 出版者・発行元
- IEEE
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 chi(2)-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.
- リンク情報
- ID情報
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- ISSN : 2475-420X
- Web of Science ID : WOS:000540384500017