Single-Trial EEG Classification via Common Spatial Patterns with Mixed Lp- and Lq-Norms

Single-Trial EEG Classification via Common Spatial Patterns with Mixed Lp- and Lq-Norms

As a multichannel spatial filtering technique, common spatial patterns (CSP) have been successfully applied in brain-computer interfaces (BCI) community based on electroencephalogram (EEG). However, it is sensitive to outliers because of the employment of the L2-norm in its formulation. It is benefi...

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Veröffentlicht in:Mathematical problems in engineering 2021-06, Vol.2021, p.1-13
Hauptverfasser: Cai, Qian, Gong, Weiqiang, Deng, Yue, Wang, Haixian
Format: Artikel
Sprache:eng
Schlagworte:
Classification
Discriminant analysis
Electroencephalography
Human-computer interface
Iterative algorithms
Iterative methods
Machine learning
Mathematical problems
Norms
Optimization
Outliers (statistics)
Robustness
Spatial filtering
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Zusammenfassung:As a multichannel spatial filtering technique, common spatial patterns (CSP) have been successfully applied in brain-computer interfaces (BCI) community based on electroencephalogram (EEG). However, it is sensitive to outliers because of the employment of the L2-norm in its formulation. It is beneficial to perform robust modelling for CSP. In this paper, we propose a robust framework, called CSP-Lp/q, by formulating the variances of two EEG classes with Lp- and Lq-norms (0
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/6645322