Smooth compression, Gallager bound and nonlinear sparse-graph codes

A. Montanari, Elchanan Mossel
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引用次数: 23

Abstract

A data compression scheme is defined to be smooth if its image (the codeword) depends gracefully on the source (the data). Smoothness is a desirable property in many practical contexts, and widely used source coding schemes lack of it. We introduce a family of smooth source codes based on sparse graph constructions, and prove them to achieve the (information theoretic) optimal compression rate for a dense set of iid sources. As a byproduct, we show how Gallager bound on sparsity can be overcome using non-linear function nodes.
平滑压缩,Gallager界和非线性稀疏图码
如果一个数据压缩方案的图像(码字)优雅地依赖于源(数据),那么它就被定义为平滑的。在许多实际情况下,平滑性是一种理想的特性,而广泛使用的源编码方案缺乏平滑性。我们引入了一组基于稀疏图构造的平滑源代码,并证明了它们对密集的id源集具有(信息论的)最优压缩率。作为副产品,我们展示了如何使用非线性函数节点克服稀疏性上的Gallager界。
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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