Author:
Ortiz Daza Camilo Andrés,Simanca H. Fredys A.,Blanco Garrido Fabian,Burgos Daniel
Reference36 articles.
1. Bodda, S., Chandranpillai, H., Viswam, P., Krishna, S., Nair, B., & Diwakar, S. (2016). Categorizing imagined right and left motor imagery BCI tasks for low-cost robotic neuroprothesis. In International Conference on Electrical, Electronics, and Optomization Techniques (ICEEOT) (pp. 3670–3673).
2. Braga, R. B., Lopes, C., & Becker, T. (2018). Round cosine transform based feature extraction of motor imagery EEG signals. In World Congress on Medical Physics and Biomedical Engineering (pp. 511–515).
3. Brockwell, P. J., & Davis, R. A. (2002). Introduction to time series and forecasting. New York: Springer.
4. Chatterjee, R., Bandyopadhyay, T., & Sanyal Kumar, D. (2016). Effects of wavelets on quality of features in motor imagery EEG signal classification. In 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) (pp. 1346–1350). Chennai, India: IEEE.
https://doi.org/10.1109/WiSPNET.2016.7566356
.
5. Chatterjee, R., Datta, A., & Kumar Sanyal, D. (2019). Ensemble learning approach to motor imagery EEG signals classification. In N. Dey, A. S. Ashour, S. Borra, & F. Shi, Machine learning in biosignal analysis and diagnostic imaging (pp. 183–208). Elsevier Inc.
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