Expectation Maximization Based PCA and Hessian LLE with Suitable Post Classifiers for Epilepsy Classification from EEG Signals

Author:

Prabhakar Sunil Kumar,Rajaguru Harikumar

Publisher

Springer International Publishing

Reference21 articles.

1. Prabhakar, S.K., Rajaguru, H.: ICA, LGE and FMI as dimensionality reduction techniques followed by GMM as post classifier for the classification of epilepsy risk levels from EEG signals. In: Proceedings of the 9th IEEE European Modelling Symposium, Madrid, Spain, 6–8 October, pp. 1–5 (2015)

2. Prabhakar, S.K., Rajaguru, H.: Application of linear graph embedding as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals. In: Proceedings of the International Conference on Graphic and Image Processing (ICGIP), Singapore, 23–25 October 2015

3. Prabhakar, S.K., Rajaguru, H.: A different approach to epilepsy risk level classification utilizing various distance measures as post classifiers. In: Proceedings of the 8th Biomedical Engineering International Conference (BMEiCON), Pattaya, Thailand, 25–27 November 2015

4. Acir, N., Oztura, I., Kuntalp, M., Baklan, B., Guzelis, C.: Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. IEEE Trans. Biomed. Eng. 52, 30–40 (2005)

5. Adjouadi, M., Cabrerizo, M., Ayala, M., Sanchez, D., Yaylali, I., Jayakar, P., Barreto, A.: A new mathematical approach based on orthogonal operators for the detection of interictal spikes in epileptogenic data. Biomed. Sci. Instrum. 40, 175–180 (2004)

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