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An efficient scheme for mental task classification utilizing reflection coefficients obtained from autocorrelation function of EEG signal
Classification of different mental tasks using electroencephalogram (EEG) signal plays an imperative part in various brain–computer interface (BCI) applications. In the design of BCI systems, features extracted from lower frequency bands of scalp-recorded EEG signals are generally considered to clas...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5893497/ https://www.ncbi.nlm.nih.gov/pubmed/29224063 http://dx.doi.org/10.1007/s40708-017-0073-7 |