An efficient scheme for mental task classification utilizing reflection coefficients obtained from autocorrelation function of EEG signal

Siuly S, Li Y (2012) Improving the separability of motor imagery EEG signals using a cross correlation-based least square support vector machine for brain–computer interface. IEEE Trans Neural Syst Rehabil Eng 20(4):526

Suk HI, Lee SW (2013) A novel Bayesian framework for discriminative feature extraction in brain–computer interfaces. IEEE Trans Pattern Anal Mach Intell 35(2):286

Yong X, Ward RK, Birch GE (2008) Sparse spatial filter optimization for EEG channel reduction in brain–computer interface. In: Proceedings ICASSP, pp 417–420

Lu H, Plataniotis KN, Venetsanopoulos AN (2009) Regularized common spatial patterns with generic learning for EEG signal classification. In: Proceedings of IEEE engineering in medicine and biology society, pp 6599–6602

Palaniappan R (2006) Utilizing gamma band to improve mental task based brain–computer interface design. IEEE Trans Neural Syst Rehabil Eng 14(3):299

Zhang L, He W, He C, Wang P (2010) Improving mental task classification by adding high frequency band information. J Med Syst 34(1):51

Liang NY, Saratchandran P, Huang GB, Sundararajan N (2006) Classification of mental tasks from EEG signals using extreme learning machine. Int J Neural Syst 16(01):29

Anderson CW, Stolz EA, Shamsunder S (1998) Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks. IEEE Trans Biomed Eng 45(3):277

Wang Q, Sourina O (2013) Real-time mental arithmetic task recognition from EEG signals. IEEE Trans Neural Syst Rehabil Eng 21(2):225

Li X, Chen X, Yan Y, Wei W, Wang ZJ (2014) Classification of EEG signals using a multiple kernel learning support vector machine. Sensors 14(7):12784

Gupta A, Agrawal R, Kaur B (2015) Performance enhancement of mental task classification using EEG signal: a study of multivariate feature selection methods. Soft Comput. 19(10):2799

Talukdar MTF, Sakib SK, Pathan NS, Fattah SA (2014) Motor imagery EEG signal classification scheme based on autoregressive reflection coefficients. In: Proceedings ICIEV, pp 1–4

Fattah S, Fatima K, Shahnaz C (2015) An approach for classifying alcoholic and non-alcoholic persons based on time domain features extracted from EEG signals. In: Proceedings WIECON-ECE, pp 479–482

Keirn ZA, Aunon JI (1990) A new mode of communication between man and his surroundings. IEEE Trans Biomed Eng 37(12):1209

Duda RO, Hart PE, Stork DG (2012) Pattern classification. Wiley, New York

Kay SM (1988) Modern spectral estimation. Pearson Education India, New Delhi

Rangayyan RM, Reddy NP (2002) Biomedical signal analysis: a case-study approach. Ann Biomed Eng 30(7):983

Kung SY (2014) Kernel methods and machine learning. Cambridge University Press