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

Zarei, Roozbeh, He, Jing, Siuly, Siuly and Zhang, Yanchun 2017, A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals, Computer methods and programs in biomedicine, vol. 146, pp. 47-57, doi: 10.1016/j.cmpb.2017.05.009.

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Title A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals
Author(s) Zarei, RoozbehORCID iD for Zarei, Roozbeh orcid.org/0000-0001-6738-334X
He, Jing
Siuly, Siuly
Zhang, Yanchun
Journal name Computer methods and programs in biomedicine
Volume number 146
Start page 47
End page 57
Total pages 11
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2017-07
ISSN 0169-2607
1872-7565
Keyword(s) Brain-computer interface (BCI)
Cross-covariance method (CCOV)
Electroencephalogram (EEG)
Feature extraction
Principal component analysis (PCA)
Science & Technology
Technology
Life Sciences & Biomedicine
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
Engineering, Biomedical
Medical Informatics
Computer Science
Engineering
Language eng
DOI 10.1016/j.cmpb.2017.05.009
Field of Research 0903 Biomedical Engineering
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2017, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30121343

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Citation counts: TR Web of Science Citation Count  Cited 10 times in TR Web of Science
Scopus Citation Count Cited 11 times in Scopus
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