Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms

One of the most popular feature extraction algorithms for brain-computer interfaces (BCI) is common spatial patterns (CSPs). Despite its known efficiency and widespread use, CSP is also known to be very sensitive to noise and prone to overfitting. To address this issue, it has been recently proposed...

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Vydáno v:	IEEE transactions on biomedical engineering Ročník 58; číslo 2; s. 355 - 362
Hlavní autoři:	Lotte, Fabien, Guan, Cuntai
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.02.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithm design and analysis Algorithms Applied sciences Artificial Intelligence Biological and medical sciences Biotechnology Brain-computer interfaces (BCI) common spatial patterns (CSP) Computer Science Computer science; control theory; systems Computer systems and distributed systems. User interface Computerized, statistical medical data processing and models in biomedicine Covariance matrix Eigenvalues and eigenfunctions Electrodes Electrodiagnosis. Electric activity recording Electroencephalography electroencephalography (EEG) Electroencephalography - methods Engineering Sciences Exact sciences and technology Humans Investigative techniques, diagnostic techniques (general aspects) Life Sciences Man-Machine Systems Medical management aid. Diagnosis aid Medical sciences Models, Neurological Nervous system Noise Pattern Recognition, Automated - methods Regression Analysis regularization Signal and Image Processing Signal Processing, Computer-Assisted Software subject-to-subject transfer Training User-Computer Interface Human regularization Theoretical study Man machine dialogue Brain-computer interfaces (BCI) Electroencephalography common spatial patterns (CSP) Pattern recognition Algorithm Design Brain-computer interface electroencephalography (EEG) Electrodiagnosis User interface subject-to-subject transfer Signal processing Biomedical engineering
ISSN:	0018-9294, 1558-2531, 1558-2531
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