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Classification of Normal and Pre-Ictal EEG Signals Using Permutation Entropies and a Generalized Linear Model as a Classifier

In this contribution, a comparison between different permutation entropies as classifiers of electroencephalogram (EEG) records corresponding to normal and pre-ictal states is made. A discrete probability distribution function derived from symbolization techniques applied to the EEG signal is used t...

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Autori principali: Francisco O. Redelico, Francisco Traversaro, María del Carmen García, Walter Silva, Osvaldo A. Rosso, Marcelo Risk
Natura: Artigo
Lingua:Inglês
Pubblicazione: MDPI AG 2017-02-01
Serie:Entropy
Soggetti:
permutation entropy
permutation min-entropy
electroencephalography
classification analysis
Accesso online:http://www.mdpi.com/1099-4300/19/2/72
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