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...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 49; no. 11; pp. 1337 - 1347 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Nov2011
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| Acceso en línea: | Ver este registro en EBSCOhost |