Dwumodułowy system do przetwarzania danych EEG z wykorzystaniem analizy czynnikowej i pseudoinwersji moore-penrose

[1]  Yuanqing Li,et al.  Sparse Representation and Its Applications in Blind Source Separation , 2003, NIPS.

[2]  P. Agostino Accardo,et al.  Use of the fractal dimension for the analysis of electroencephalographic time series , 1997, Biological Cybernetics.

[3]  Lei Xu,et al.  Dual multivariate auto-regressive modeling in state space for temporal signal separation , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[4]  Sz. Paszkiel,et al.  The application of electroencephalographic signals in the aspect of controlling a mobile robot for measurements of partial discharges , 2010 .

[5]  S. Paszkiel,et al.  The use of Brain Computer Interfaces in control processes based on the industrial PC in terms of the methods of EEG signal analyses , 2013 .

[6]  Andrzej Cichocki,et al.  Csiszár's Divergences for Non-negative Matrix Factorization: Family of New Algorithms , 2006, ICA.

[7]  Sergio Cruces,et al.  Robust blind source separation algorithms using cumulants , 2002, Neurocomputing.

[8]  Karl J. Friston,et al.  A neural mass model for MEG/EEG: coupling and neuronal dynamics , 2003, NeuroImage.

[9]  Yuanqing Li,et al.  Analysis of Sparse Representation and Blind Source Separation , 2004, Neural Computation.

[10]  Vasilios N. Katsikis,et al.  Fast computing of the Moore-Penrose inverse matrix , 2008 .

[11]  Szczepan Paszkiel Augmented Reality of Technological Environment in Correlation with Brain Computer Interfaces for Control Processes , 2014, Recent Advances in Automation, Robotics and Measuring Techniques.

[12]  Andrzej Cichocki,et al.  New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[13]  Yuanqing Li,et al.  Blind estimation of channel parameters and source components for EEG signals: a sparse factorization approach , 2006, IEEE Transactions on Neural Networks.

[14]  Vasilios N. Katsikis,et al.  An improved method for the computation of the Moore-Penrose inverse matrix , 2011, Appl. Math. Comput..

[15]  E. Oja,et al.  Independent Component Analysis , 2013 .

[16]  T. Lagerlund,et al.  Spatial filtering of multichannel electroencephalographic recordings through principal component analysis by singular value decomposition. , 1997, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[17]  Chih-Jen Lin,et al.  Projected Gradient Methods for Nonnegative Matrix Factorization , 2007, Neural Computation.

[18]  S. Paszkiel The population modeling of neuronal cell fractions for the use of controlling a mobile robot , 2013 .

[19]  Sergio Cruces,et al.  An iterative inversion approach to blind source separation , 2000, IEEE Trans. Neural Networks Learn. Syst..