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Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination
Using machine-learning methodologies to analyze EEG signals becomes increasingly attractive for recognizing human emotions because of the objectivity of physiological data and the capability of the learning principles on modeling emotion classifiers from heterogeneous features. However, the conventi...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385370/ https://www.ncbi.nlm.nih.gov/pubmed/28443015 http://dx.doi.org/10.3389/fnbot.2017.00019 |