Spatial Filtering for EEG-Based Regression Problems in Brain–Computer Interface (BCI)
Electroencephalogram (EEG) signals are frequently used in brain-computer interfaces (BC!s), but they are easily contaminated by artifacts and noise, so preprocessing must be done before they are fed into a machine learning algorithm for classification or regression. Spatial filters have been widely...
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| Main Authors: | , , , , |
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| Format: | Artigo |
| Language: | English |
| Published: |
2017
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| Online Access: | https://doi.org/10.1109/tfuzz.2017.2688423 |
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