Removing electroencephalographic artifacts by blind source separation.
暂无分享,去创建一个
T. Sejnowski | M. McKeown | T. Jung | S. Makeig | Te-Won Lee | C. Humphries | T. W. Lee | V. Iragui | M. Mckeown | Colin Humphries
[1] D. Overton,et al. Distribution of eye movement and eyeblink potentials over the scalp. , 1969, Electroencephalography and clinical neurophysiology.
[2] S. Hillyard,et al. Eye movement artifact in the CNV. , 1970, Electroencephalography and clinical neurophysiology.
[3] P. Lang,et al. The effects of eye fixation and stimulus and response location on the contingent negative variation (CNV). , 1973, Biological psychology.
[4] H. Moldofsky,et al. A spectral method for removing eye movement artifacts from the EEG. , 1978, Electroencephalography and clinical neurophysiology.
[5] T. Gasser,et al. Correction of EOG artifacts in event-related potentials of the EEG: aspects of reliability and validity. , 1982, Psychophysiology.
[6] J. C. Woestenburg,et al. The removal of the eye-movement artifact from the EEG by regression analysis in the frequency domain , 1983, Biological Psychology.
[7] E Donchin,et al. A new method for off-line removal of ocular artifact. , 1983, Electroencephalography and clinical neurophysiology.
[8] J. Kenemans,et al. Removal of the ocular artifact from the EEG: a comparison of time and frequency domain methods with simulated and real data. , 1991, Psychophysiology.
[9] P. Berg,et al. Dipole models of eye movements and blinks. , 1991, Electroencephalography and clinical neurophysiology.
[10] J. Nadal. Non linear neurons in the low noise limit : a factorial code maximizes information transferJean , 1994 .
[11] J. Nadal,et al. Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer Network 5 , 1994 .
[12] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[13] Andrzej Cichocki,et al. Robust learning algorithm for blind separation of signals , 1994 .
[14] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[15] Tzyy-Ping Jung,et al. Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.
[16] Andrzej Cichocki,et al. A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.
[17] Yoram Baram,et al. Multidimensional density shaping by sigmoids , 1996, IEEE Trans. Neural Networks.
[18] Barak A. Pearlmutter,et al. Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA , 1996, NIPS.
[19] A. J. Bell,et al. Blind Separation of Event-Related Brain Responses into Independent Components , 1996 .
[20] Dinh-Tuan Pham,et al. Blind separation of instantaneous mixture of sources via an independent component analysis , 1996, IEEE Trans. Signal Process..
[21] R. Lambert. Multichannel blind deconvolution: FIR matrix algebra and separation of multipath mixtures , 1996 .
[22] Jean-François Cardoso,et al. Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..
[23] Ehud Weinstein,et al. Multichannel signal separation: methods and analysis , 1996, IEEE Trans. Signal Process..
[24] C. Fyfe,et al. Generalised independent component analysis through unsupervised learning with emergent Bussgang properties , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).
[25] Erkki Oja,et al. A class of neural networks for independent component analysis , 1997, IEEE Trans. Neural Networks.
[26] Shun-ichi Amari,et al. Stability Analysis Of Adaptive Blind Source Separation , 1997 .
[27] 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.
[28] Tzyy-Ping Jung,et al. Independent Component Analysis of Electroencephalographic and Event-Related Potential Data , 1998 .
[29] Tzyy-Ping Jung,et al. Analyzing and Visualizing Single-Trial Event-Related Potentials , 1998, NIPS.
[30] Mark A. Girolami,et al. An Alternative Perspective on Adaptive Independent Component Analysis Algorithms , 1998, Neural Computation.
[31] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources , 1999, Neural Comput..
[32] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.
[33] Terrence J. Sejnowski,et al. Independent Component Analysis of Simulated ERP Data , 2000 .
[34] Thomas P. Flanders,et al. Performing Organization Name(s) and Address(es) , 2001 .
[35] B. AfeArd. CALCULATING THE SINGULAR VALUES AND PSEUDOINVERSE OF A MATRIX , 2022 .