The Interplay Between Information and Estimation Measures
The Interplay Between Information and Estimation Measures
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DOI：
10.1561/2000000018
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发表时间：
2012-01-01
影响因子：
--
通讯作者：
Verdu, Sergio
中科院分区：
文献类型：
--
作者：
Guo, Dongning;Shamai (Shitz), Shlomo;Verdu, Sergio
这本专著调查的信息措施和估计措施之间的相互作用，以及它们的应用。重点是公式表示的主要信息措施，如熵，互信息和相对熵的最小均方误差估计时，可实现的高斯噪声污染的随机变量。这些关系导致了广泛的应用，从连续时间非线性滤波中的普遍关系到通信系统中的最优功率分配，到信息论中重要结果的简化证明，如熵功率不等式和多用户信息论中的逆。
This monograph surveys the interactions between information measures and estimation measures as well as their applications. The emphasis is on formulas that express the major information measures, such as entropy, mutual information and relative entropy in terms of the minimum mean square error achievable when estimating random variables contaminated by Gaussian noise. These relationships lead to wide applications ranging from a universal relationship in continuous-time nonlinear filtering to optimal power allocation in communication systems, to the simplified proofs of important results in information theory such as the entropy power inequality and converses in multiuser information theory.