On The Significance Of Binning In A Scaling-law Sense

K. Eswaran, M. Gastpar
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引用次数: 4

Abstract

An efficient distributed source coding system with two encoders and dependent data streams must remove two kinds of redundancy: redundancy in each stream and between the two streams. The striking result of Slepian and Wolf showed that the latter can be eliminated even if each encoder only observes one of the source streams. The coding technique that permits to achieve this is often referred to as "binning." In large source networks, binning can result in considerable savings in terms of encoding rate. The focus of this paper is on the scaling-law behavior, i.e., the characteristic performance in the limit as the source network size tends to infinity. For paradigmatic network topologies, we analyze the rate savings through binning, and we show that in some cases of interest, binning is scaling-law irrelevant.
论标度律意义上的分形的意义
具有两个编码器和依赖数据流的高效分布式源编码系统必须消除两种冗余:每个流中的冗余和两个流之间的冗余。Slepian和Wolf的惊人结果表明,即使每个编码器只观察一个源流,后者也可以消除。允许实现这一点的编码技术通常被称为“分码”。在大型源网络中,分码可以在编码速率方面节省大量费用。本文的重点是研究标度律行为,即源网络规模趋于无穷大时的极限下的特征性能。对于范例网络拓扑,我们分析了通过分组节省的速率,并表明在一些感兴趣的情况下,分组与比例律无关。
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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