Detection of epileptical seizures based on alpha band statistical features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-020-07542-5.pdf
Reference45 articles.
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3. Sharma, R. R., & Pachori, R. B. (2017). Time–frequency representation using IEVDHM–HT with application to classification of epileptic EEG signals. IET Science, Measurement & Technology, 12(1), 72–82.
4. Boashash, B., Azemi, G., & Ali Khan, N. (2015). Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection. Pattern Recognition.
5. Mursalin, M., Zhang, Y., Chen, Y., & Chawla, N. V. (2017). Automated epileptic seizure detection using improved correlation-based feature selection with random forest classifier. Neurocomputing, 241, 204–214.
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