Using Probabilistic Direct Multi-class Support Vector Machines to Improve Mental States Based-Brain Computer Interface
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-03577-8_35
Reference22 articles.
1. Vaid, R.S., Singh, P., Kaur, C.: EEG signal analysis for BCI interface: a review. In: IEEE Transaction on Advanced Computing and Communication Technologies, pp. 143–147 (2015)
2. Prashant, P., Joshi, A., Gandhi, V.: Brain computer interface: a review. In: 5th Nirma University International Conference on Engineering, pp. 1–6. IEEE (2015)
3. Gupta, A., Agrawal, R.K., Kaur, B.: Performance enhancement of mental task classification using EEG signal: a study of multivariate feature selection methods. Soft Comput. 19, 2799–2812 (2015)
4. Hendel, M., Benyettou, A., Hendel, F.: Hybrid self organizing map and probabilistic quadratic loss multi-class support vector machine for mental tasks classification. Inform. Med. Unlocked 4, 1–9 (2016)
5. Gupta, A., Kirar, J.S.: A novel approach for extracting feature from EEG signal for mental task classification. In: IEEE Transaction on Computing and Network Communications, pp. 829–832 (2015)
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