Sphere-covering and measure concentration as source coding theorems

Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252) Pub Date : 2001-06-24 DOI:10.1109/ISIT.2001.936031

Ioannis Kontoyiannis

引用次数: 0

Abstract

We state and solve a general version of the rate-distortion problem. We show that its answer contains, as corollaries: (i) Stein's lemma in hypothesis testing; (ii) Shannon's (1959) lossy source coding theorem; and (iii) new converses to measure-concentration inequalities.

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作为源编码定理的球覆盖和测度浓度

我们陈述并解决了一般版本的汇率扭曲问题。作为推论，我们证明其答案包含:(i)假设检验中的Stein引理;(ii)香农(1959)有损源编码定理;(三)衡量集中度不平等的新反义词。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)

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