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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...
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| Pubblicato in: | Neurocomputing |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier Science Publishers
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7086459/ https://ncbi.nlm.nih.gov/pubmed/32226230 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neucom.2018.04.087 |
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