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

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...

Full description

Bibliographic Details
Main Authors: Francisco O. Redelico, Francisco Traversaro, María del Carmen García, Walter Silva, Osvaldo A. Rosso, Marcelo Risk
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Entropy
Subjects:
permutation entropy
permutation min-entropy
electroencephalography
classification analysis
Online Access:http://www.mdpi.com/1099-4300/19/2/72

Internet

http://www.mdpi.com/1099-4300/19/2/72

Similar Items