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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...
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| Pubblicato in: | J Med Biol Eng |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer Berlin Heidelberg
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5840222/ https://ncbi.nlm.nih.gov/pubmed/29541014 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s40846-017-0239-z |
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