The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces
<b>Background:</b> In motor imagery brain–computer interface (MI-BCI) research, electroencephalogram (EEG) signals are complex and nonlinear. This complexity and nonlinearity render signal processing and classification challenging when employing traditional linear methods. Information entropy, with...
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| Autori principali: | , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
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MDPI AG
2025-02-01
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| Serie: | Brain Sciences |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2076-3425/15/2/168 |
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