A comparison of univariate, vector, bilinear autoregressive, and band power features for brain–computer interfaces

Selecting suitable feature types is crucial to obtain good overall brain–computer interface performance. Popular feature types include logarithmic band power (logBP), autoregressive (AR) parameters, time-domain parameters, and wavelet-based methods. In this study, we focused on different variants of...

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Detalles Bibliográficos
Autores principales: Brunner, Clemens, Billinger, Martin, Vidaurre, Carmen, Neuper, Christa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2011
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208819/
https://www.ncbi.nlm.nih.gov/pubmed/21947797
http://dx.doi.org/10.1007/s11517-011-0828-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208819/
https://www.ncbi.nlm.nih.gov/pubmed/21947797
http://dx.doi.org/10.1007/s11517-011-0828-x

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