凸度量的信息集中

2016 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2016-08-11 DOI:10.1109/ISIT.2016.7541475

Jiange Li, M. Fradelizi, M. Madiman

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引用次数: 6

摘要

对于欧几里德空间上的凸概率测度，得到了信息量的急剧指数偏差估计和变异性的急剧界。在某种意义上，这些提供了凸测度的非渐近均分性质，即使在没有平稳型假设的情况下。

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Information concentration for convex measures

Sharp exponential deviation estimates for the information content as well as a sharp bound on the varentropy are obtained for convex probability measures on Euclidean spaces. These provide, in a sense, a nonasymptotic equipartition property for convex measures even in the absence of stationarity-type assumptions.

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2016 IEEE International Symposium on Information Theory (ISIT)

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