A Grey Wolf Optimisation-Based Framework for Emotion Recognition on Electroencephalogram Data
Author:
Affiliation:
1. Department of Instrumentation, Kurukshetra University, Kurukshetra, Haryana 136119, India
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/59/1/214/pdf
Reference17 articles.
1. EEG Signal Accuracy for Emotion Detection Using Multiple Classification Algorithm;Jaswal;Harbin Gongye Daxue Xuebao/J. Harbin Inst. Technol.,2022
2. Jaswal, R.A., Dhingra, S., and Kumar, J.D. (2022). Recent Trends in Electronics and Communication, Springer.
3. A channel selection method for emotion recognition from EEG based on swarm-intelligence algorithms;Yildirim;IEEE Access,2021
4. Ghane, P., Hossain, G., and Tovar, A. (2015, January 15–19). Robust understanding of EEG patterns in silent speech. Proceedings of the 2015 National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA.
5. Cîmpanu, C., Ferariu, L., Ungureanu, F., and Dumitriu, T. (2017, January 19–21). Genetic feature selection for large EEG data with commutation between multiple classifiers. Proceedings of the 2017 21st International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania.
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