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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主要な著者:	Francisco O. Redelico, Francisco Traversaro, María del Carmen García, Walter Silva, Osvaldo A. Rosso, Marcelo Risk
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2017-02-01
シリーズ:	Entropy
主題:	permutation entropy permutation min-entropy electroencephalography classification analysis
オンライン･アクセス:	http://www.mdpi.com/1099-4300/19/2/72
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