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Sparse Logistic Regression With L(1/2) Penalty for Emotion Recognition in Electroencephalography Classification
Emotion recognition based on electroencephalography (EEG) signals is a current focus in brain-computer interface research. However, the classification of EEG is difficult owing to large amounts of data and high levels of noise. Therefore, it is important to determine how to effectively extract featu...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427509/ https://www.ncbi.nlm.nih.gov/pubmed/32848688 http://dx.doi.org/10.3389/fninf.2020.00029 |