Blind source separation by entropy rate minimization

被引：5

作者：

Gómez-Herrero G. ^{[1
]}

Rutanen K. ^{[1
]}

Egiazarian K. ^{[1
]}

机构：

[1] Department of Signal Processing, Tampere University of Technology, Tampere

来源：

IEEE Signal Processing Letters | 2010年 / 17卷 / 02期

关键词：

Blind source separation; Electroencephalography; Independent component analysis;

D O I：

10.1109/LSP.2009.2035731

中图分类号：

学科分类号：

摘要：

An algorithm for the blind separation of mutually independent and/or temporally correlated sources is presented in this letter. The algorithm is closely related to the maximum likelihood approach based on entropy rate minimization but uses a simpler contrast function that can be accurately and efficiently estimated using nearest-neighbor distances. The advantages of the new algorithm are highlighted using simulations and real electroencephalographic data. © 2009 IEEE.

引用

页码：153 / 156

页数：3

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