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...

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Detalles Bibliográficos
Autores principales: Yin, Zhong, Wang, Yongxiong, Liu, Li, Zhang, Wei, Zhang, Jianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Neuroscience
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

Internet

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

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