On Renyi Measures and Hypothesis Testing

被引：0

作者：

Shayevitz, Ofer ^{[1
]}

机构：

[1] Univ Calif San Diego, Informat Theory & Applicat Ctr, La Jolla, CA 92093 USA

来源：

2011 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT) | 2011年

关键词：

CODING THEOREM; INFORMATION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We provide a variational characterization for the various Renyi information measures via their Shannon counterparts, and demonstrate how properties of the former can be recovered from first principle via the associated properties of the latter. Motivated by this characterization, we give a new operational interpretation for the Renyi divergence in a two-sensor composite hypothesis testing framework.

引用

页码：894 / 898

页数：5

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