An Extremal Inequality Motivated by Multiterminal Information Theoretic Problems

Tie Liu, P. Viswanath
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引用次数: 208

Abstract

We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problem. As a corollary, this inequality yields a generalization of the classical vector entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing differential entropy of a sum of jointly distributed random variables, generalizing a classical result of Cover and Zhang.
基于多终端信息理论问题的一个极值不等式
我们证明了一个新的极值不等式,该不等式由矢量高斯广播信道和具有单个二次失真约束问题的分布式信源编码驱动。作为一个推论,这个不等式产生了经典向量熵-功率不等式(EPI)的推广。作为另一个推论,这个不等式揭示了如何最大化联合分布随机变量和的微分熵,推广了Cover和Zhang的经典结果。
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