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Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms
Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI p...
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| Publicado no: | Comput Intell Neurosci |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Hindawi
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5569879/ https://ncbi.nlm.nih.gov/pubmed/28874909 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/2727856 |
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