EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN) to discover unknown fea...

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Detalles Bibliográficos
Autores principales: Jirayucharoensak, Suwicha, Pan-Ngum, Setha, Israsena, Pasin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165739/
https://www.ncbi.nlm.nih.gov/pubmed/25258728
http://dx.doi.org/10.1155/2014/627892

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165739/
https://www.ncbi.nlm.nih.gov/pubmed/25258728
http://dx.doi.org/10.1155/2014/627892

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