Tutorial of EM algorithm and its application：part Ⅰ

doi:10.3778/j.issn.1002-8331.2008.29.016

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (29): 61-64.DOI: 10.3778/j.issn.1002-8331.2008.29.016

• 理论研究 • Previous Articles Next Articles

Tutorial of EM algorithm and its application：part Ⅰ

LI Chang-li,SHEN Yu-li

School of Information Engineering，Guangdong Ocean University，Zhanjiang，Guangdong 524088，China

Received:2007-11-20 Revised:2008-01-14 Online:2008-10-11 Published:2008-10-11
Contact: LI Chang-li

期望最大算法及其应用（1）

李昌利,沈玉利

广东海洋大学信息学院，广东　湛江 524088

通讯作者: 李昌利

Abstract

Abstract: EM algorithm is an effective method for maximum-likelihood estimate（MLE），which is mainly used to estimate parameters of incomplete data.On the one hand，by assuming the existence of hidden variable in EM algorithm，the likelihood function are greatly simplified；on the other hand，some special parameters estimation can be easily realized by virtue of EM algorithm.MLE is a common parameters estimation method and EM algorithm makes its application more extensive.This tutorial is organized from users’ points of view and its content is self-contained.

Key words: expectation-maximization（EM）, maximum likelihood estimation（MLE）, incomplete data, hidden variable

摘要： EM算法是实现极大似然估计的一种有效方法，主要用于非完全数据的参数估计。它通过假设隐变量的存在，极大地简化了似然方程；对于一些特殊的参数估计问题，利用EM算法也很容易实现。而极大似然估计是一种常用的参数估计方法，EM算法使其应用更加广泛。文章从应用者的角度出发，内容是自包含的。

关键词: 期望最大（EM）, 极大似然估计（MLE）, 不完全数据, 隐变量

LI Chang-li,SHEN Yu-li. Tutorial of EM algorithm and its application：part Ⅰ[J]. Computer Engineering and Applications, 2008, 44(29): 61-64.

李昌利,沈玉利. 期望最大算法及其应用（1）[J]. 计算机工程与应用, 2008, 44(29): 61-64.

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Tutorial of EM algorithm and its application：part Ⅰ

期望最大算法及其应用（1）

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