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

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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Bibliographic Details
Main Authors: Jonatan Lerga, Nicoletta Saulig, Ljubiša Stanković, Damir Seršić
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Mathematics
Subjects:
Rényi entropy
short-term Rényi entropy
instantaneous frequency (IF) estimation
EEG signals
time–frequency signal analysis
Online Access:https://www.mdpi.com/2227-7390/9/4/451

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