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具有因果解码器边信息的逐次细化的指数型强逆定理

Exponential Strong Converse for Successive Refinement with Causal Decoder Side Information.

作者信息

Zhou Lin, Hero Alfred

机构信息

Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.

出版信息

Entropy (Basel). 2019 Apr 17;21(4):410. doi: 10.3390/e21040410.

Abstract

We consider the -user successive refinement problem with causal decoder side information and derive an exponential strong converse theorem. The rate-distortion region for the problem can be derived as a straightforward extension of the two-user case by Maor and Merhav (2008). We show that for any rate-distortion tuple outside the rate-distortion region of the -user successive refinement problem with causal decoder side information, the joint excess-distortion probability approaches one exponentially fast. Our proof follows by judiciously adapting the recently proposed strong converse technique by Oohama using the information spectrum method, the variational form of the rate-distortion region and Hölder's inequality. The lossy source coding problem with causal decoder side information considered by El Gamal and Weissman is a special case ( k = 1 ) of the current problem. Therefore, the exponential strong converse theorem for the El Gamal and Weissman problem follows as a corollary of our result.

摘要

我们考虑具有因果解码器边信息的 - 用户逐次细化问题,并推导了一个指数型强逆定理。该问题的率失真区域可以作为Maor和Merhav(2008年)两用户情形的直接扩展来推导。我们表明,对于具有因果解码器边信息的 - 用户逐次细化问题的率失真区域之外的任何率失真元组,联合超额失真概率以指数速度快速趋近于1。我们的证明通过明智地采用Oohama最近提出的使用信息谱方法、率失真区域的变分形式和赫尔德不等式的强逆技术来完成。El Gamal和Weissman所考虑的具有因果解码器边信息的有损源编码问题是当前问题的一个特殊情况(k = 1)。因此,El Gamal和Weissman问题的指数型强逆定理作为我们结果的一个推论得出。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dccc/7514900/4e655c395141/entropy-21-00410-g001.jpg

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