文章基本信息

标题：An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms
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作者：Dominic Langlois ; Sylvain Chartier ; Dominique Gosselin 等
期刊名称：Tutorials in Quantitative Methods for Psychology
电子版ISSN：1913-4126
出版年度：2010
卷号：6
期号：1
页码：31-38
DOI：10.20982/tqmp.06.1.p031
出版社：Université de Montréal
摘要：This paper presents an introduction to independent component analysis (ICA). Unlike principal component analysis, which is based on the assumptions of uncorrelatedness and normality, ICA is rooted in the assumption of statistical independence. Foundations and basic knowledge necessary to understand the technique are provided hereafter. Also included is a short tutorial illustrating the implementation of two ICA algorithms (FastICA and InfoMax) with the use of the Mathematica software.