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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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| Vydáno v: | Front Neurosci |
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| Hlavní autoři: | , , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Frontiers Media S.A.
2019
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6901997/ https://ncbi.nlm.nih.gov/pubmed/31849587 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2019.01275 |
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