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Energy Distribution Evaluation Using Renyi Entropy Measures With Application in EEG Data Analysis
Author(s) -
Theodor D. Popescu
Publication year - 2021
Publication title -
wseas transactions on signal processing
Language(s) - English
Resource type - Journals
eISSN - 2224-3488
pISSN - 1790-5052
DOI - 10.37394/232014.2021.17.14
Subject(s) - electroencephalography , computer science , pattern recognition (psychology) , entropy (arrow of time) , rényi entropy , artificial intelligence , energy distribution , artifact (error) , energy (signal processing) , statistics , mathematics , principle of maximum entropy , psychology , physics , atomic physics , quantum mechanics , psychiatry
The ”corrected” EEG recordings, after artifact removing, may be the subject of further investigations, for example segmentation and energy distribution, resulting new informa- tion to be used for feature extraction, of great help for medical diagnosis. The paper presents a generally method for energy distribution evalua- tion using measures of R´enyi entropy. The pre- sented approach ensures the possibility of quan- titative analysis of the information contained in time-frequency distribution of EEG signals. The proposed procedure is applied with good results in the analysis of a sample lowpass event-related potentials (ERP) data, collected from 13 scalp and 1 EOG electrodes.

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