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Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree
This paper presents an accurate nonlinear classification method that can help physicians diagnose seizure in electroencephalographic (EEG) signal characterized by a disturbance in temporal and spectral content. This is accomplished by applying four steps. First, different EEG signals containing heal...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840222/ https://www.ncbi.nlm.nih.gov/pubmed/29541014 http://dx.doi.org/10.1007/s40846-017-0239-z |