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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...
Autores principales: | Raza, Haider, Rathee, Dheeraj, Zhou, Shang-Ming, Cecotti, Hubert, Prasad, Girijesh |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science Publishers
2019
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Materias: | |
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 |
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