A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals

Article ID	Journal	Published Year	Pages	File Type
4958075	Computer Methods and Programs in Biomedicine	2017	34 Pages	PDF

Abstract

Conclusions: The proposed feature extraction method is very effective for getting representatives information from mental states EEG signals in BCI applications and reducing the computational complexity of classifiers by reducing the number of extracted features.

Keywords

00-01 99-00 Principal component analysis (PCA)Feature extraction Brain-computer interface (BCI)Electroencephalogram (EEG)

Related Topics

Physical Sciences and Engineering Computer Science Computer Science (General)

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A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals

Authors

Roozbeh Zarei, Jing He, Siuly Siuly, Yanchun Zhang,