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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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| Foilsithe in: | Front Neurosci |
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| Main Authors: | , , , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
Frontiers Media S.A.
2020
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| Ábhair: | |
| Rochtain Ar Líne: | 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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