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A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification

OBJECTIVE: Electroencephalogram (EEG) based brain–computer interfaces (BCI) in motor imagery (MI) have developed rapidly in recent years. A reliable feature extraction method is essential because of a low signal-to-noise ratio (SNR) and time-dependent covariates of EEG signals. Because of efficient...

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Detalles Bibliográficos
Autores principales:	Wu, Hao, Niu, Yi, Li, Fu, Li, Yuchen, Fu, Boxun, Shi, Guangming, Dong, Minghao
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2019
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901997/ https://www.ncbi.nlm.nih.gov/pubmed/31849587 http://dx.doi.org/10.3389/fnins.2019.01275

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