由非周期噪声和侧信息问题引起的熵放大

A. Cohen, R. Zamir
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引用次数: 0

摘要

一个阿贝尔群的子集如果对所有非零都有唯一的差异。当被视为可加性噪声时,具有唯一差异的集对于一大类输入分布尽可能地放大输出熵,这被称为熵放大特性。非周期(噪声)分布是研究边信息问题中速率损失的极端情况,例如在编码器处已知加性干扰的信道编码和在解码器处具有边信息的有损源编码。解码器输出重构,这是满足失真约束所必需的。重构具有一定失真的干净源相当于重构具有相同失真的加密源。使用EAP,速率损失可以任意大,也可以任意接近100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy amplification by aperiodic noise and side information problems
A subset of an Abelian group has unique differences if for all nonzeros. when viewed as additive noise, sets with unique differences amplify the output entropy as much as possible for a large class of input distributions, which is known as entropy amplification property. Aperiodic (noise) distributions arise as extreme cases in the investigation of the rate loss in side information problems such as channel coding with additive interference known at the encoder and lossy source coding with side information at the decoder. The decoder outputs a reconstruction, which is required to satisfy a distortion constraint. Reconstructing the clean source with some distortion is equivalent to reconstructing the encrypted source with the same distortion. Using the EAP, the rate loss can be arbitrarily large and arbitrarily close to 100%.
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