Electroencephalogram-Based Motor Imagery Classification Using Deep Residual Convolutional Networks
The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types with high accuracy, a classification methodology using the wavelet packet decomposition (WPD) and t...
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| Autori principali: | , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2021-11-01
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| Serie: | Frontiers in Neuroscience |
| Soggetti: | |
| Accesso online: | https://www.frontiersin.org/articles/10.3389/fnins.2021.774857/full |
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