On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics
暂无分享,去创建一个
Christian Jutten | Marco Congedo | Cédric Gouy-Pailler | C. Jutten | M. Congedo | C. Gouy-Pailler | Cédric Gouy-Pailler
[1] Xi-Lin Li,et al. Nonorthogonal Joint Diagonalization Free of Degenerate Solution , 2007, IEEE Transactions on Signal Processing.
[2] F. L. D. Silva,et al. Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.
[3] Serge Dégerine,et al. A Comparative Study of Approximate Joint Diagonalization Algorithms for Blind Source Separation in Presence of Additive Noise , 2007, IEEE Transactions on Signal Processing.
[4] Ricardo Vigário,et al. Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions , 2003, J. Mach. Learn. Res..
[5] A. Pérez-Villalba. Rhythms of the Brain, G. Buzsáki. Oxford University Press, Madison Avenue, New York (2006), Price: GB £42.00, p. 448, ISBN: 0-19-530106-4 , 2008 .
[6] Abdeldjalil Aïssa-El-Bey,et al. Underdetermined Blind Separation of Nondisjoint Sources in the Time-Frequency Domain , 2007, IEEE Transactions on Signal Processing.
[7] Jan Beran,et al. Statistics for long-memory processes , 1994 .
[8] Fabian J. Theis,et al. Blind signal separation into groups of dependent signals using joint block diagonalization , 2005, 2005 IEEE International Symposium on Circuits and Systems.
[9] Christian Jutten,et al. Space or time adaptive signal processing by neural network models , 1987 .
[10] Motoaki Kawanabe,et al. A resampling approach to estimate the stability of one-dimensional or multidimensional independent components , 2002, IEEE Transactions on Biomedical Engineering.
[11] Dinh-Tuan Pham,et al. Blind separation of instantaneous mixtures of nonstationary sources , 2001, IEEE Trans. Signal Process..
[12] Andrzej Cichocki,et al. Adaptive blind signal and image processing , 2002 .
[13] El Mostafa Fadaili,et al. Nonorthogonal Joint Diagonalization/Zero Diagonalization for Source Separation Based on Time-Frequency Distributions , 2007, IEEE Transactions on Signal Processing.
[14] Arie Yeredor,et al. Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation , 2002, IEEE Trans. Signal Process..
[15] Zhi-Lin Zhang,et al. Morphologically constrained ICA for extracting weak temporally correlated signals , 2008, Neurocomputing.
[16] Marco Congedo,et al. Subspace Projection Filters for Real-Time Brain Electromagnetic Imaging , 2006, IEEE Transactions on Biomedical Engineering.
[17] Fernando H. Lopes da Silva,et al. Functional localization of brain sources using EEG and/or MEG data: volume conductor and source models. , 2004 .
[18] Theo Gasser,et al. Correction of muscle artefacts in the EEG power spectrum , 2005, Clinical Neurophysiology.
[19] F. H. Lopes da Silva,et al. Computer-assisted EEG diagnosis: pattern recognition and brain mapping , 1998 .
[20] C. Joyce,et al. Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. , 2004, Psychophysiology.
[21] Cuntai Guan,et al. Feature Selection Based on Fisher Ratio and Mutual Information Analyses for Robust Brain Computer Interface , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[22] Mercedes Atienza,et al. Muscle Artifact Removal from Human Sleep EEG by Using Independent Component Analysis , 2008, Annals of Biomedical Engineering.
[23] Terrence J. Sejnowski,et al. Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data , 2003, Neural Networks.
[24] Robert Plonsey,et al. Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .
[25] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[26] A. Yeredor. Blind separation of Gaussian sources via second-order statistics with asymptotically optimal weighting , 2000, IEEE Signal Processing Letters.
[27] Andrzej Cichocki,et al. Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications , 2002 .
[28] F. H. Lopes da Silva,et al. Event-related potentials: methodology and quantification , 1998 .
[29] Matthew T. Sutherland,et al. Reliable detection of bilateral activation in human primary somatosensory cortex by unilateral median nerve stimulation , 2006, NeuroImage.
[30] L. Fety,et al. New methods for signal separation , 1988 .
[31] J. Gotman,et al. Removal of EMG and ECG artifacts from EEG based on wavelet transform and ICA , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[32] Jean-Franois Cardoso. High-Order Contrasts for Independent Component Analysis , 1999, Neural Computation.
[33] Ernst Fernando Lopes Da Silva Niedermeyer,et al. Electroencephalography, basic principles, clinical applications, and related fields , 1982 .
[34] P. Welch. The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .
[35] Antoine Souloumiac,et al. Blind source detection and separation using second order non-stationarity , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.
[36] Matthew T. Sutherland,et al. Validation of SOBI components from high-density EEG , 2005, NeuroImage.
[37] J.C. Mosher,et al. Multiple dipole modeling and localization from spatio-temporal MEG data , 1992, IEEE Transactions on Biomedical Engineering.
[38] Klaus Obermayer,et al. Quadratic optimization for simultaneous matrix diagonalization , 2006, IEEE Transactions on Signal Processing.
[39] P. Rossini,et al. Functional source separation from magnetoencephalographic signals , 2006, Human brain mapping.
[40] R. Greenblatt,et al. Local linear estimators for the bioelectromagnetic inverse problem , 2005, IEEE Transactions on Signal Processing.
[41] Armando Malanda,et al. Independent Component Analysis as a Tool to Eliminate Artifacts in EEG: A Quantitative Study , 2003, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[42] Andrzej Cichocki,et al. Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis , 2002, Biological Cybernetics.
[43] Yimin Zhang,et al. Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions , 2006, EURASIP J. Adv. Signal Process..
[44] Arie Yeredor,et al. A fast approximate joint diagonalization algorithm using a criterion with a block diagonal weight matrix , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[45] G.F. Inbar,et al. An improved P300-based brain-computer interface , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[46] Christopher J. James,et al. Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis , 2003, IEEE Transactions on Biomedical Engineering.
[47] Adel Belouchrani,et al. A one step time-frequency blind identification , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..
[48] Rémi Gribonval,et al. A survey of Sparse Component Analysis for blind source separation: principles, perspectives, and new challenges , 2006, ESANN.
[49] S P Fitzgibbon,et al. Removal of EEG Noise and Artifact Using Blind Source Separation , 2007, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[50] B. Thompson. Canonical Correlation Analysis , 1984 .
[51] Lang Tong,et al. BLIND ESTIMATION OF CORRELATED SOURCE SIGNALS , 1990, 1990 Conference Record Twenty-Fourth Asilomar Conference on Signals, Systems and Computers, 1990..
[52] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[53] J. Cardoso,et al. Blind beamforming for non-gaussian signals , 1993 .
[54] Barry D. Van Veen,et al. MEG and EEG source localization in beamspace , 2006, IEEE Transactions on Biomedical Engineering.
[55] Paul Van de Heyninga,et al. Correlation between Independent Components of scalp EEG and intracranial EEG ( iEEG ) time series , 2007 .
[56] Klaus-Robert Müller,et al. Enhancing the signal-to-noise ratio of ICA-based extracted ERPs , 2006, IEEE Transactions on Biomedical Engineering.
[57] Dinh Tuan Pham,et al. Blind separation of instantaneous mixture of sources via the Gaussian mutual information criterion , 2000, 2000 10th European Signal Processing Conference.
[58] Soo-Young Lee. Blind Source Separation and Independent Component Analysis: A Review , 2005 .
[59] Miguel Angel Mañanas,et al. A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: A simulation case , 2008, Comput. Biol. Medicine.
[60] Matthew T. Sutherland,et al. Recovery of correlated neuronal sources from EEG: The good and bad ways of using SOBI , 2005, NeuroImage.
[61] Lang Tong,et al. Indeterminacy and identifiability of blind identification , 1991 .
[62] T. Sejnowski,et al. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects , 2000, Clinical Neurophysiology.
[63] P. Nunez,et al. Source analysis of EEG oscillations using high-resolution EEG and MEG. , 2006, Progress in brain research.
[64] C.J. James,et al. On the use of Spectrally Constrained ICA applied to single-channel Ictal EEG recordings within a Dynamical Embedding Framework , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[65] Lucas C. Parra,et al. Blind Source Separation via Generalized Eigenvalue Decomposition , 2003, J. Mach. Learn. Res..
[66] Lars Kai Hansen,et al. Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG , 2007, Neural Computation.
[67] Andreas Ziehe,et al. Blind Source Separation Techniques for Decomposing Event-Related Brain Signals , 2004, Int. J. Bifurc. Chaos.
[68] Kiyotoshi Matsuoka,et al. A neural net for blind separation of nonstationary signals , 1995, Neural Networks.
[69] Andrzej Cichocki,et al. Independent component analysis for unaveraged single-trial MEG data decomposition and single-dipole source localization , 2002, Neurocomputing.
[70] Andrzej Cichocki,et al. Second Order Nonstationary Source Separation , 2002, J. VLSI Signal Process..
[71] Gwen A. Frishkoff,et al. Automated protocol for evaluation of electromagnetic component separation (APECS): Application of a framework for evaluating statistical methods of blink extraction from multichannel EEG , 2007, Clinical Neurophysiology.
[72] Steven G. Johnson,et al. The Design and Implementation of FFTW3 , 2005, Proceedings of the IEEE.
[73] R N Vigário,et al. Extraction of ocular artefacts from EEG using independent component analysis. , 1997, Electroencephalography and clinical neurophysiology.
[74] Franca Tecchio,et al. Functional source separation applied to induced visual gamma activity , 2008, Human brain mapping.
[75] Schuster,et al. Separation of a mixture of independent signals using time delayed correlations. , 1994, Physical review letters.
[76] R. Fisher,et al. Epileptic seizure disorders , 1985, Journal of Neurology.
[77] S. J. Roberts,et al. Independent Component Analysis: Source Assessment Separation, a Bayesian Approach , 1998 .
[78] M. Corbetta,et al. Electrophysiological signatures of resting state networks in the human brain , 2007, Proceedings of the National Academy of Sciences.
[79] Andreas Ziehe,et al. A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation , 2004, J. Mach. Learn. Res..
[80] F. H. Lopes da Silva,et al. Biophysical aspects of EEG and magnetoencephalogram generation , 1998 .
[81] Yan Wang,et al. Contrasting single-trial ERPs between experimental manipulations: Improving differentiability by blind source separation , 2006, NeuroImage.
[82] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[83] Peter F. Driessen,et al. Independent component analysis and clustering improve signal-to-noise ratio for statistical analysis of event-related potentials , 2007, Clinical Neurophysiology.
[84] Moeness G. Amin,et al. Blind source separation based on time-frequency signal representations , 1998, IEEE Trans. Signal Process..
[85] Eric Moulines,et al. A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..
[86] Christopher J. James,et al. Extracting Rhythmic Brain Activity for Brain-Computer Interfacing through Constrained Independent Component Analysis , 2007, Comput. Intell. Neurosci..
[87] I F Gorodnitsky,et al. Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.
[88] Christopher J. James,et al. On Semi-Blind Source Separation Using Spatial Constraints With Applications in EEG Analysis , 2006, IEEE Transactions on Biomedical Engineering.
[89] 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.
[90] Lang Tong,et al. Waveform-preserving blind estimation of multiple independent sources , 1993, IEEE Trans. Signal Process..
[91] Yannick Deville,et al. Temporal and time-frequency correlation-based blind source separation methods. Part I: Determined and underdetermined linear instantaneous mixtures , 2007, Signal Process..
[92] Fabian J. Theis,et al. On the use of joint diagonalization in blind signal processing , 2006, 2006 IEEE International Symposium on Circuits and Systems.
[93] Wim Van Paesschen,et al. Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram , 2006, IEEE Transactions on Biomedical Engineering.
[94] E. Whitham,et al. Scalp electrical recording during paralysis: Quantitative evidence that EEG frequencies above 20Hz are contaminated by EMG , 2007, Clinical Neurophysiology.
[95] M. Wax,et al. A least-squares approach to joint diagonalization , 1997, IEEE Signal Processing Letters.
[96] F. H. Lopes da Silva,et al. Functional localization of brain sources using EEG and/or MEG data: volume conductor and source models. , 2004, Magnetic resonance imaging.
[97] L. Trahms,et al. Single evoked somatosensory MEG responses extracted by time delayed decorrelation , 2005, IEEE Transactions on Signal Processing.
[98] Patrick Berg,et al. Artifact Correction of the Ongoing EEG Using Spatial Filters Based on Artifact and Brain Signal Topographies , 2002, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[99] J. Cardoso. On the Performance of Orthogonal Source Separation Algorithms , 1994 .
[100] Fabian J. Theis,et al. Uniqueness of complex and multidimensional independent component analysis , 2004, Signal Process..
[101] Andreas Ziehe,et al. TDSEP — an efficient algorithm for blind separation using time structure , 1998 .
[102] Arie Yeredor,et al. Asymptotically Optimal Blind Separation of Parametric Gaussian Sources , 2004, ICA.
[103] Ramesh Srinivasan,et al. Identification of wave‐like spatial structure in the SSVEP: Comparison of simultaneous EEG and MEG , 2007, Statistics in medicine.
[104] Ignace Lemahieu,et al. Removing Ocular Movement Artefacts by a Joint Smoothened Subspace Estimator , 2007, Comput. Intell. Neurosci..
[105] P. Comon,et al. Ica: a potential tool for bci systems , 2008, IEEE Signal Processing Magazine.
[106] T. Ens,et al. Blind signal separation : statistical principles , 1998 .
[107] J. Sarvas. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. , 1987, Physics in medicine and biology.
[108] Serge Dégerine,et al. Second-order blind separation of sources based on canonical partial innovations , 2000, IEEE Trans. Signal Process..
[109] Fabian J. Theis,et al. Pivot Selection Strategies in Jacobi Joint Block-Diagonalization , 2007, ICA.
[110] Dinh Tuan Pham,et al. Joint Approximate Diagonalization of Positive Definite Hermitian Matrices , 2000, SIAM J. Matrix Anal. Appl..
[111] Aapo Hyvärinen,et al. Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.
[112] G. Darmois,et al. Analyse générale des liaisons stochastiques: etude particulière de l'analyse factorielle linéaire , 1953 .
[113] Wei Lu,et al. Approach and applications of constrained ICA , 2005, IEEE Transactions on Neural Networks.
[114] D. Pham,et al. Exploiting source non stationary and coloration in blind source separation , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).
[115] Bhaskar D. Rao,et al. Sparse solutions to linear inverse problems with multiple measurement vectors , 2005, IEEE Transactions on Signal Processing.
[116] Jean-François Cardoso,et al. Multidimensional independent component analysis , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[117] Patrick Suppes,et al. Single-Trial Classification of MEG Recordings , 2007, IEEE Transactions on Biomedical Engineering.
[118] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[119] Lei Ding,et al. Motor imagery classification by means of source analysis for brain–computer interface applications , 2004, Journal of neural engineering.
[120] Joep J. M. Kierkels,et al. A model-based objective evaluation of eye movement correction in EEG recordings , 2006, IEEE Transactions on Biomedical Engineering.
[121] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[122] A. Cichocki,et al. Blind separation of nonstationary sources in noisy mixtures , 2000 .
[123] Wolfgang Rosenstiel,et al. Online Artifact Removal for Brain-Computer Interfaces Using Support Vector Machines and Blind Source Separation , 2007, Comput. Intell. Neurosci..