Two Measures of Dependence
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Author / Producer
Date
2019-08
Publication Type
Journal Article
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yes
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Abstract
Two families of dependence measures between random variables are introduced. They are based on the Rényi divergence of order α and the relative α -entropy, respectively, and both dependence measures reduce to Shannon’s mutual information when their order α is one. The first measure shares many properties with the mutual information, including the data-processing inequality, and can be related to the optimal error exponents in composite hypothesis testing. The second measure does not satisfy the data-processing inequality, but appears naturally in the context of distributed task encoding.
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published
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Journal / series
Volume
21 (8)
Pages / Article No.
778
Publisher
MDPI
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Edition / version
Methods
Software
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Date collected
Date created
Subject
data processing; dependence measure; relative α-entropy; Rényi divergence; Rényi entropy
Organisational unit
03529 - Lapidoth, Amos / Lapidoth, Amos