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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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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Springer-Verlag
2011
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3208819/ https://ncbi.nlm.nih.gov/pubmed/21947797 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11517-011-0828-x |
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