DocumentCode :
1385182
Title :
L1-Norm-Based Common Spatial Patterns
Author :
Wang, Haixian ; Tang, Qin ; Zheng, Wenming
Author_Institution :
Key Lab. of Child Dev. & Learning Sci. of Minist. of Educ., Southeast Univ., Nanjing, China
Volume :
59
Issue :
3
fYear :
2012
fDate :
3/1/2012 12:00:00 AM
Firstpage :
653
Lastpage :
662
Abstract :
Common spatial patterns (CSP) is a commonly used method of spatial filtering for multichannel electroencephalogram (EEG) signals. The formulation of the CSP criterion is based on variance using L2-norm, which implies that CSP is sensitive to outliers. In this paper, we propose a robust version of CSP, called CSP-L1, by maximizing the ratio of filtered dispersion of one class to the other class, both of which are formulated by using L1-norm rather than L2-norm. The spatial filters of CSP-L1 are obtained by introducing an iterative algorithm, which is easy to implement and is theoretically justified. CSP-L1 is robust to outliers. Experiment results on a toy example and datasets of BCI competitions demonstrate the efficacy of the proposed method.
Keywords :
brain-computer interfaces; electroencephalography; iterative methods; medical signal processing; spatial filters; BCI; CSP; EEG; L1-norm; brain-computer interfaces; common spatial patterns; electroencephalogram; iterative algorithm; spatial filtering; Dispersion; Eigenvalues and eigenfunctions; Electroencephalography; Integrated circuits; Iterative methods; Robustness; Vectors; Brain-computer interfaces; CSP-L1; L1-norm; common spatial patterns (CSP); robust modeling; Algorithms; Artificial Intelligence; Brain Mapping; Computer Simulation; Electroencephalography; Humans; Models, Theoretical; Pattern Recognition, Automated; Reproducibility of Results; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2011.2177523
Filename :
6092465
Link To Document :
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