Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals

In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to...

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Detalles Bibliográficos
Autores principales: Adam, Asrul, Ibrahim, Zuwairie, Mokhtar, Norrima, Shapiai, Mohd Ibrahim, Mubin, Marizan, Saad, Ismail
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025417/
https://www.ncbi.nlm.nih.gov/pubmed/27652153
http://dx.doi.org/10.1186/s40064-016-3277-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025417/
https://www.ncbi.nlm.nih.gov/pubmed/27652153
http://dx.doi.org/10.1186/s40064-016-3277-z

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