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遍历源的雷尼熵低复杂度估计方法

Low Complexity Estimation Method of Rényi Entropy for Ergodic Sources.

作者信息

Kim Young-Sik

机构信息

Department of Information and Communication Engineering, Chosun University, 309 Pilmoondae-ro Dong-gu, Gwangju 61452, Korea.

出版信息

Entropy (Basel). 2018 Aug 31;20(9):657. doi: 10.3390/e20090657.

Abstract

Since the entropy is a popular randomness measure, there are many studies for the estimation of entropies for given random samples. In this paper, we propose an estimation method of the Rényi entropy of order α . Since the Rényi entropy of order α is a generalized entropy measure including the Shannon entropy as a special case, the proposed estimation method for Rényi entropy can detect any significant deviation of an ergodic stationary random source's output. It is shown that the expected test value of the proposed scheme is equivalent to the Rényi entropy of order α . After deriving a general representation of parameters of the proposed estimator, we discuss on the particular orders of Rényi entropy such as α → 1 , α = 1 / 2 , and α = 2 . Because the Rényi entropy of order 2 is the most popular one, we present an iterative estimation method for the application with stringent resource restrictions.

摘要

由于熵是一种常用的随机性度量,因此有许多关于给定随机样本熵估计的研究。在本文中,我们提出了一种α阶Rényi熵的估计方法。由于α阶Rényi熵是一种广义熵度量,香农熵是其特殊情况,因此所提出的Rényi熵估计方法可以检测遍历平稳随机源输出的任何显著偏差。结果表明所提方案的期望测试值等同于α阶Rényi熵。在推导了所提估计器参数的一般表示后,我们讨论了Rényi熵的特定阶数,如α→1、α = 1/2和α = 2。由于二阶Rényi熵是最常用的一种,我们提出了一种适用于资源严格受限情况的迭代估计方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a8/7513180/04f42dbf540d/entropy-20-00657-g001.jpg

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