Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface

The non-stationary nature of electroencephalography (EEG) signals makes an EEG-based brain-computer interface (BCI) a dynamic system, thus improving its performance is a challenging task. In addition, it is well-known that due to non-stationarity based covariate shifts, the input data distributions...

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Detalles Bibliográficos
Autores principales: Raza, Haider, Rathee, Dheeraj, Zhou, Shang-Ming, Cecotti, Hubert, Prasad, Girijesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Publishers 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086459/
https://www.ncbi.nlm.nih.gov/pubmed/32226230
http://dx.doi.org/10.1016/j.neucom.2018.04.087

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086459/
https://www.ncbi.nlm.nih.gov/pubmed/32226230
http://dx.doi.org/10.1016/j.neucom.2018.04.087

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