Rule-Based EEG Classifier Utilizing Local Entropy of Time–Frequency Distributions

Electroencephalogram (EEG) signals are known to contain signatures of stimuli that induce brain activities. However, detecting these signatures to classify captured EEG waveforms is one of the most challenging tasks of EEG analysis. This paper proposes a novel time–frequency-based method for EEG ana...

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Main Authors: Jonatan Lerga, Nicoletta Saulig, Ljubiša Stanković, Damir Seršić
פורמט: Article
שפה:English
יצא לאור: MDPI AG 2021-02-01
סדרה:Mathematics
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גישה מקוונת:https://www.mdpi.com/2227-7390/9/4/451

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