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
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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