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Gray-Wyner and Slepian-Wolf Guessing

机译:Gray-Wyner和Slepian-Wolf猜测

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摘要

We study the guessing variants of two distributed source coding problems: the Gray-Wyner network and the Slepian-Wolf network. Building on the former, we propose a new definition of the Rényi common information as the least attainable common rate in the Gray-Wyner guessing problem under the no-excess-rate constraint. We then provide a variational characterization of this quantity. In the Slepian-Wolf setting, we follow up the work of Bracher-Lapidoth-Pfister with the case where the expected number of guesses need not converge to one but must be dominated by some given exponential.
机译:我们研究了两个分布式源编码问题的猜测变体:Gray-Wyner网络和Slepian-Wolf网络。在前者的基础上,我们提出了对Rényi公共信息的新定义,将其定义为在不存在超额利率约束的情况下Gray-Wyner猜想问题中可获得的最低公共利率。然后,我们提供此数量的变化特征。在Slepian-Wolf设置中,我们对Bracher-Lapidoth-Pfister的工作进行了跟进,在这种情况下,预期猜测的数量不必收敛到一个,而必须由某些给定的指数控制。

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