Nonnegative matrix factorization for motor imagery EEG classification

被引：0
|
作者：
Lee, Hyekyoung
Cichocki, Andrzej
Choi, Seungjin
机构：
[1] Pohang Univ Sci & Technol, Dept Comp Sci, Pohang 790784, South Korea
[2] RIKEN, Lab Adv Brain Signal Proc, Brain Sci Inst, Wako, Saitama 3510198, Japan
来源：
ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2 | 2006年 / 4132卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present a method of feature extraction for motor imagery single trial EEG classification, where we exploit nonnegative matrix factorization (NMF) to select discriminative features in the time-frequency representation of EEG. Experimental results with motor imagery EEG data in BCI competition 2003, show that the method indeed finds meaningful EEG features automatically, while some existing methods should undergo cross-validation to find them.
引用
收藏
页码：250 / 259
页数：10
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