On approximating the rate regions for lossy source coding with coded and uncoded side information

Wei-Hsin Gu, S. Jana, M. Effros
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引用次数: 10

Abstract

We derive new algorithms for approximating the rate regions for a family of source coding problems that includes lossy source coding, lossy source coding with uncoded side information at the receiver (the Wyner-Ziv problem), and an achievability bound for lossy source coding with coded side in formation at the receiver. The new algorithms generalize a recent approximation algorithm by Go and Effros from lossless to lossy coding. In each case, prior information theoretic descriptions of the desired regions are available but difficult to evaluate for example sources due to their dependence on auxiliary random variables. Our algorithm builds a linear program whose solution is no less than the desired lower bound and no greater than (1 + isin) times that optimal value. These guarantees are met even when the optimal value is unknown. Here isin > 0 is a parameter chosen by the user; the algorithmic complexity grows as O(isin-M) as e approaches 0, where M > 4 is a constant that depends on the source coding problem and the alphabet sizes of the sources.
用已编码和未编码的边信息逼近有损源编码的速率区域
我们推导了一组源编码问题的近似速率区域的新算法,这些问题包括有损源编码,在接收器处具有未编码侧信息的有损源编码(Wyner-Ziv问题),以及在接收器处具有编码侧信息的有损源编码的可实现性边界。新算法将Go和Effros最近提出的从无损编码到有损编码的近似算法进行了推广。在每种情况下,期望区域的先验信息理论描述是可用的,但难以评估,例如,由于它们依赖于辅助随机变量。我们的算法构建了一个线性程序,其解不小于期望的下界,且不大于最优值的(1 + isin)倍。即使在最优值未知的情况下,也能满足这些保证。在>中,0是用户选择的参数;当e接近0时,算法复杂度随着O(isin-M)而增长,其中M > 4是一个常数,它取决于源编码问题和源的字母大小。
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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