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An Intelligent EEG Classification Methodology Based on Sparse Representation Enhanced Deep Learning Networks
The classification of electroencephalogram (EEG) signals is of significant importance in brain–computer interface (BCI) systems. Aiming to achieve intelligent classification of EEG types with high accuracy, a classification methodology using sparse representation (SR) and fast compression residual c...
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| Veröffentlicht in: | Front Neurosci |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Frontiers Media S.A.
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7596898/ https://ncbi.nlm.nih.gov/pubmed/33177970 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2020.00808 |
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