[1] T. Alotaiby, F. E. A. El-Samie, S. A. Alshebeili, and I. Ahmad, "A review of channel selection algorithms for EEG signal processing," EURASIP Journal on Advances in Signal Processing, vol. 2015, no. 1, p. 66, 2015.
[2] Z. Zhang and K. K. Parhi, "Seizure prediction using long-term fragmented intracranial canine and human EEG recordings," in Signals, Systems and Computers, 2016 50th Asilomar Conference on, 2016, pp. 361-365: IEEE.
[3] K. Gadhoumi, J.-M. Lina, F. Mormann, and J. Gotman, "Seizure prediction for therapeutic devices: A review," Journal of neuroscience methods, vol. 260, pp. 270-282, 2016.
[4] Harvard Health Publications, Harvard Medical School, 2014. Seizure overview. http://www.health.harvard.edu/mind-and-mood/seizure-overview.
[5] A. Theodorakopoulou, "Machine learning data preparation for epileptic seizures prediction," 2017.
[6] Y. Park, L. Luo, K. K. Parhi, and T. Netoff, "Seizure prediction with spectral power of EEG using cost‐sensitive support vector machines," Epilepsia, vol. 52, no. 10, pp. 1761-1770, 2011.
[7] A. T. Tzallas, M. G. Tsipouras, and D. I. J. I. t. o. i. t. i. b. Fotiadis, "Epileptic seizure detection in EEGs using time-frequency analysis," vol. 13, no. 5, pp. 703-710, 2009.
[8] H. Adeli, S. Ghosh-Dastidar, and N. J. I. T. o. B. E. Dadmehr, "A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy," vol. 54, no. 2, pp. 205-211, 2007.
[9] R.J. Oweis, E. W. J. B. e. o. Abdulhay, "Seizure classification in EEG signals utilizing Hilbert-Huang transform," vol. 10, no. 1, p. 38, 2011.
[10]V. Bajaj and R. B. J. I. T. o. I. T. i. B. Pachori, "Classification of seizure and nonseizure EEG signals using empirical mode decomposition," vol. 16, no. 6, pp. 1135-1142, 2012.
[11]S. S. Alam, M. I. H. J. I. j. o. b. Bhuiyan, and h. informatics, "Detection of seizure and epilepsy using higher order statistics in the EMD domain," vol. 17, no. 2, pp. 312-318, 2013.
[12]M. Peker, B. Sen, D. J. I. j. o. b. Delen, and h. informatics, "A novel method for automated diagnosis of epilepsy using complex-valued classifiers," vol. 20, no. 1, pp. 108-118, 2016.
[13]G. Wang et al., "Epileptic seizure detection based on partial directed coherence analysis," vol. 20, no. 3, pp. 873-879, 2016.
[14]K. Samiee, P. Kovacs, M.J.I.t.o.B.E. Gabbouj, "Epileptic seizure classification of EEG time-series using rational discrete short-time Fourier transform," vol. 62, no. 2, pp. 541-552, 2015.
[15]A. B. Das, M. I. H. Bhuiyan, S. S. J. S. Alam, Image, and V. Processing, "Classification of EEG signals using normal inverse Gaussian parameters in the dual-tree complex wavelet transform domain for seizure detection," vol. 10, no. 2, pp. 259-266, 2016.
[16]I. Guler E.D.J.I.T.o.I. T. i. B. Ubeyli, "Multiclass support vector machines for EEG-signals classification," vol. 11, no. 2, pp. 117-126, 2007.
[17]L. Guo, D. Rivero, J. Dorado, J. R. Rabunal, and A. J. J. o. n. m. Pazos, "Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks," vol. 191, no. 1, pp. 101-109, 2010.
[18]P. Swami, T. K. Gandhi, B. K. Panigrahi, M. Tripathi, and S. J. E. S. w. A. Anand, "A novel robust diagnostic model to detect seizures in electroencephalography," vol. 56, pp. 116-130, 2016.
[19]A. R. Hassan, S. Siuly, Y. J. C. m. Zhang, and p. i. biomedicine, "Epileptic seizure detection in EEG signals using tunable-Q factor wavelet transform and bootstrap aggregating," vol. 137, pp. 247-259, 2016.
[20]M. Sharma, R. B. Pachori, and U. R. Acharya, "A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension," Pattern Recognition Letters, vol. 94, pp. 172-179, 2017.
[21]X. Pang, "Seizure forecasting," Stanford University, Autumn 2014.
[22]N. D. Truong, A. D. Nguyen, L. Kuhlmann, M. R. Bonyadi, J. Yang, and O. Kavehei, "A Generalised Seizure Prediction with Convolutional Neural Networks for Intracranial and Scalp Electroencephalogram Data Analysis," arXiv preprint arXiv:1707.01976, 2017.
[23]Y. Park, L. Luo, K. K. Parhi, and T. Netoff, "Seizure prediction with spectral power of EEG using cost‐sensitive support vector machines," Epilepsia, vol. 52, no. 10, pp. 1761-1770, 2011.
[24]U. R. Acharya, S. L. Oh, Y. Hagiwara, J. H. Tan, and H. Adeli, "Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals," Computers in biology and medicine, vol. 100, pp. 270-278, 2018.
[25]T. F. Bastos-Filho, A. Ferreira, A. C. Atencio, S. Arjunan, and D. Kumar, "Evaluation of feature extraction techniques in emotional state recognition," in Intelligent human computer interaction (IHCI), 2012 4th international conference on, 2012, pp. 1-6: IEEE.
[26]S. Mallat and Z. Zhang, "Matching pursuit with time-frequency dictionaries," Courant Institute of Mathematical Sciences New York United States1993.
[27]Naderahmadian, Yashar, Soosan Beheshti, and Mohammad Ali Tinati. “Correlation based online dictionary learning algorithm.” IEEE Transactions on signal processing 64.3 (2016): 592-602.
[28]Z. Mousavi, T. Yousefi Rezaii, S. Sheykhivand, A. Farzamnia, and S. N. Razavi. "Deep convolutional neural network for classification of sleep stages from single-channel EEG signals." Journal of neuroscience methods 324 (2019): 108312.