Differential evolution with temporal difference Q-learning based feature selection for motor imagery EEG data
暂无分享,去创建一个
Pratyusha Rakshit | Amit Konar | Swagatam Das | Atulya K. Nagar | D. N. Tibarewala | Saugat Bhattacharyya | Swagatam Das | A. Nagar | A. Konar | D. Tibarewala | P. Rakshit | S. Bhattacharyya
[1] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[2] J. Wolpaw,et al. Brain–computer interfaces in neurological rehabilitation , 2008, The Lancet Neurology.
[3] M Congedo,et al. A review of classification algorithms for EEG-based brain–computer interfaces , 2007, Journal of neural engineering.
[4] G. Pfurtscheller,et al. Motor imagery activates primary sensorimotor area in humans , 1997, Neuroscience Letters.
[5] Swagatam Das,et al. Automatic Clustering Using an Improved Differential Evolution Algorithm , 2007 .
[6] G Pfurtscheller,et al. Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[7] Pratyusha Rakshit,et al. DE-TDQL: An adaptive memetic algorithm , 2012, 2012 IEEE Congress on Evolutionary Computation.
[8] R. Storn,et al. Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .
[9] Alain Rakotomamonjy,et al. Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances , 2005, ICANN.
[10] R. Andersen,et al. Selecting the signals for a brain–machine interface , 2004, Current Opinion in Neurobiology.
[11] B. Ripley,et al. Pattern Recognition , 1968, Nature.
[12] HansenPer Christian. The truncated SVD as a method for regularization , 1987 .
[13] M.-C. Su,et al. A new cluster validity measure and its application to image compression , 2004, Pattern Analysis and Applications.
[14] Donald G. Childers,et al. Modern Spectrum Analysis , 1978 .
[15] Amit Konar,et al. Performance analysis of left/right hand movement classification from EEG signal by intelligent algorithms , 2011, 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB).
[16] A. Kai Qin,et al. Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.
[17] E Donchin,et al. Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[18] Andrew B. Schwartz,et al. Brain-Controlled Interfaces: Movement Restoration with Neural Prosthetics , 2006, Neuron.
[19] S.X. Yang,et al. A Knowledge Based GA for Path Planning of Multiple Mobile Robots in Dynamic Environments , 2006, 2006 IEEE Conference on Robotics, Automation and Mechatronics.
[20] Yew-Soon Ong,et al. Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.
[21] Amit Konar,et al. Computational Intelligence: Principles, Techniques and Applications , 2005 .
[22] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[23] William Z Rymer,et al. Guest Editorial Brain–Computer Interface Technology: A Review of the Second International Meeting , 2001 .
[24] H. Abdi,et al. Principal component analysis , 2010 .
[25] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..