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
收藏
页码：153 / 156
页数：3
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