模拟源信息测度的通用估计

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Foundations and Trends in Communications and Information Theory Pub Date : 2009-05-26 DOI:10.1561/0100000021

Qing Wang, Sanjeev R. Kulkarni, Sergio Verdú

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引用次数: 56

摘要

本专著提出了对连续字母源的信息测度的普遍估计的概述。特别注意了基于独立和同分布(i.i.d)数据的互信息和发散估计。综述了插件方法、基于分区的算法、最近邻算法以及其他方法，特别关注一致性、收敛速度和实验性能。

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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Universal Estimation of Information Measures for Analog Sources

This monograph presents an overview of universal estimation of information measures for continuous-alphabet sources. Special attention is given to the estimation of mutual information and divergence based on independent and identically distributed (i.i.d.) data. Plug-in methods, partitioning-based algorithms, nearest-neighbor algorithms as well as other approaches are reviewed, with particular focus on consistency, speed of convergence and experimental performance.

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来源期刊

Foundations and Trends in Communications and Information Theory COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

7.90

自引率

0.00%

发文量

期刊介绍： Foundations and Trends® in Communications and Information Theory publishes survey and tutorial articles in the following topics: - Coded modulation - Coding theory and practice - Communication complexity - Communication system design - Cryptology and data security - Data compression - Data networks - Demodulation and Equalization - Denoising - Detection and estimation - Information theory and statistics - Information theory and computer science - Joint source/channel coding - Modulation and signal design - Multiuser detection - Multiuser information theory