Handbook of Blind Source Separation: Independent Component Analysis and Applications

Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, RD algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communicationsShows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications

[1]  穂鷹 良介 Non-Linear Programming の計算法について , 1963 .

[2]  D. Cohen Magnetoencephalography: Evidence of Magnetic Fields Produced by Alpha-Rhythm Currents , 1968, Science.

[3]  E. Sowton Primer of Vectorcardiography , 1973 .

[4]  城所 良明,et al.  The Salk Institute for Biological Studies(話題) , 1975 .

[5]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[6]  Ronald W. Schafer,et al.  Digital Processing of Speech Signals , 1978 .

[7]  Philip E. Gill,et al.  Practical optimization , 1981 .

[8]  Tony F. Chan,et al.  An Improved Algorithm for Computing the Singular Value Decomposition , 1982, TOMS.

[9]  Dimitri P. Bertsekas,et al.  Constrained Optimization and Lagrange Multiplier Methods , 1982 .

[10]  Gene H. Golub,et al.  Matrix computations , 1983 .

[11]  Jan A. Kors,et al.  Adaptive Gaussian filtering in routine ECG/VCG analysis , 1986, IEEE Trans. Acoust. Speech Signal Process..

[12]  John Princen,et al.  Analysis/Synthesis filter bank design based on time domain aliasing cancellation , 1986, IEEE Trans. Acoust. Speech Signal Process..

[13]  P. McCullagh Tensor Methods in Statistics , 1987 .

[14]  M. Basseville Distance measures for signal processing and pattern recognition , 1989 .

[15]  Ronald R. Coifman,et al.  Wavelet analysis and signal processing , 1990 .

[16]  Edward R. S. Pearson,et al.  The multiresolution Fourier transform and its application to polyphonic audio analysis , 1991 .

[17]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[18]  Roman A. Polyak,et al.  Modified barrier functions (theory and methods) , 1992, Math. Program..

[19]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

[20]  Andrzej Cichocki,et al.  Robust learning algorithm for blind separation of signals , 1994 .

[21]  Robert Plonsey,et al.  Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .

[22]  L. Lathauwer,et al.  Fetal electrocardiogram extraction by source subspace separation , 1995 .

[23]  Tzyy-Ping Jung,et al.  Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.

[24]  Balas K. Natarajan,et al.  Sparse Approximate Solutions to Linear Systems , 1995, SIAM J. Comput..

[25]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[26]  Antoine Souloumiac,et al.  Jacobi Angles for Simultaneous Diagonalization , 1996, SIAM J. Matrix Anal. Appl..

[27]  Barak A. Pearlmutter,et al.  Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA , 1996, NIPS.

[28]  Sun-Yuan Kung,et al.  Principal Component Neural Networks: Theory and Applications , 1996 .

[29]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[30]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[31]  Erkki Oja,et al.  Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings , 1997, NIPS.

[32]  R N Vigário,et al.  Extraction of ocular artefacts from EEG using independent component analysis. , 1997, Electroencephalography and clinical neurophysiology.

[33]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[34]  Bhaskar D. Rao,et al.  Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm , 1997, IEEE Trans. Signal Process..

[35]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[36]  S. Mallat,et al.  Adaptive greedy approximations , 1997 .

[37]  Richard M. Leahy,et al.  Source localization using recursively applied and projected (RAP) MUSIC , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[38]  Pierre Comon,et al.  Improved contrast dedicated to blind separation in communications , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[39]  S Makeig,et al.  Blind separation of auditory event-related brain responses into independent components. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[40]  Juan K. Lin,et al.  Faithful Representation of Separable Distributions , 1997, Neural Computation.

[41]  Michael Zibulevsky,et al.  Penalty/Barrier Multiplier Methods for Convex Programming Problems , 1997, SIAM J. Optim..

[42]  J. Lacoume,et al.  Statistiques d'ordre supérieur pour le traitement du signal , 1997 .

[43]  Philippe Garat,et al.  Blind separation of mixture of independent sources through a quasi-maximum likelihood approach , 1997, IEEE Trans. Signal Process..

[44]  Andreas Ziehe,et al.  TDSEP { an e(cid:14)cient algorithm for blind separation using time structure , 1998 .

[45]  Yehoshua Y. Zeevi,et al.  Nonseparable two-dimensional multiwavelet transform for image coding and compression , 1998, Electronic Imaging.

[46]  J. Westgate,et al.  Do Fetal Electrocardiogram PR-RR Changes Reflect Progressive Asphyxia after Repeated Umbilical Cord Occlusion in Fetal Sheep? , 1998, Pediatric Research.

[47]  J. O. Wisbeck,et al.  Application of neural networks to separate interferences and ECG signals , 1998, Proceedings of the 1998 Second IEEE International Caracas Conference on Devices, Circuits and Systems. ICCDCS 98. On the 70th Anniversary of the MOSFET and 50th of the BJT. (Cat. No.98TH8350).

[48]  Jean-Francois Cardoso,et al.  Blind signal separation: statistical principles , 1998, Proc. IEEE.

[49]  Allan Kardec Barros,et al.  Application of ICA in the Separation of Breathing Artifacts in ECG Signal , 1998, ICONIP.

[50]  T. Sejnowski,et al.  Human Brain Mapping 6:368–372(1998) � Independent Component Analysis of fMRI Data: Examining the Assumptions , 2022 .

[51]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[52]  S Makeig,et al.  Analysis of fMRI data by blind separation into independent spatial components , 1998, Human brain mapping.

[53]  S. Mallat A wavelet tour of signal processing , 1998 .

[54]  S. Lévy,et al.  Atrial fibrillation: current knowledge and recommendations for management. Working Group on Arrhythmias of the European Society of Cardiology. , 1998, European heart journal.

[55]  K. Kreutz-Delgado,et al.  Convex/Schur-Convex (CSC) Log-Priors and Sparse Coding , 1999 .

[56]  Terrence J. Sejnowski,et al.  Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources , 1999, Neural Comput..

[57]  Asoke K. Nandi,et al.  Blind separation of independent sources for virtually any source probability density function , 1999, IEEE Trans. Signal Process..

[58]  M. Junghöfer,et al.  The polar average reference effect: a bias in estimating the head surface integral in EEG recording , 1999, Clinical Neurophysiology.

[59]  M. Hulle Clustering approach to square and non-square blind source separation , 1999 .

[60]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.

[61]  Bruno A. Olshausen,et al.  PROBABILISTIC FRAMEWORK FOR THE ADAPTATION AND COMPARISON OF IMAGE CODES , 1999 .

[62]  Jean-Franois Cardoso High-Order Contrasts for Independent Component Analysis , 1999, Neural Computation.

[63]  Terrence J. Sejnowski,et al.  Blind source separation of more sources than mixtures using overcomplete representations , 1999, IEEE Signal Processing Letters.

[64]  Pascal Chevalier,et al.  Optimal separation of independent narrow-band sources: Concept and performance , 1999, Signal Process..

[65]  Jean-Marc Vesin,et al.  Observer of autonomic cardiac outflow based on blind source separation of ECG parameters , 2000, IEEE Transactions on Biomedical Engineering.

[66]  T. Sejnowski,et al.  Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects , 2000, Clinical Neurophysiology.

[67]  J. Millet-Roig,et al.  Atrial activity extraction based on blind source separation as an alternative to QRST cancellation for atrial fibrillation analysis , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[68]  Joos Vandewalle,et al.  Fetal electrocardiogram extraction by blind source subspace separation , 2000, IEEE Transactions on Biomedical Engineering.

[69]  Terrence J. Sejnowski,et al.  Learning Overcomplete Representations , 2000, Neural Computation.

[70]  Barak A. Pearlmutter,et al.  Blind source separation by sparse decomposition , 2000, SPIE Defense + Commercial Sensing.

[71]  Radu Balan,et al.  Statistical properties of STFT ratios for two channel systems and applications to blind source separation , 2000 .

[72]  Erkki Oja,et al.  Independent component approach to the analysis of EEG and MEG recordings , 2000, IEEE Transactions on Biomedical Engineering.

[73]  Özgür Yilmaz,et al.  Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[74]  P. Langley,et al.  Frequency analysis of atrial fibrillation , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[75]  Justinian P. Rosca,et al.  REAL-TIME TIME-FREQUENCY BASED BLIND SOURCE SEPARATION , 2001 .

[76]  L. Vielva,et al.  UNDERDETERMINED BLIND SOURCE SEPARATION USING A PROBABILISTIC SOURCE SPARSITY MODEL , 2001 .

[77]  Xiaoming Huo,et al.  Uncertainty principles and ideal atomic decomposition , 2001, IEEE Trans. Inf. Theory.

[78]  Guy Carrault,et al.  Atrial activity enhancement by Wiener filtering using an artificial neural network , 2001, IEEE Transactions on Biomedical Engineering.

[79]  Asoke K. Nandi,et al.  Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation , 2001, IEEE Transactions on Biomedical Engineering.

[80]  V. Fuster,et al.  ACC/AHA/ESC guidelines for the management of patients with atrial fibrillation , 2001 .

[81]  T. Sejnowski,et al.  Analysis and visualization of single‐trial event‐related potentials , 2001, Human brain mapping.

[82]  Barak A. Pearlmutter,et al.  Blind Source Separation via Multinode Sparse Representation , 2001, NIPS.

[83]  Barak A. Pearlmutter,et al.  Blind Source Separation by Sparse Decomposition in a Signal Dictionary , 2001, Neural Computation.

[84]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[85]  FROM BLIND SOURCE SEPARATION TO BLIND SOURCE CANCELLATION IN THE UNDERDETERMINED CASE : A NEW APPROACH BASED ON TIME-FREQUENCY ANALYSIS , 2001 .

[86]  Pierre Comon,et al.  From source separation to blind equalization, contrast-based approaches , 2001 .

[87]  Michael Zibulevsky,et al.  Underdetermined blind source separation using sparse representations , 2001, Signal Process..

[88]  Leif Sörnmo,et al.  Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation , 2001, IEEE Transactions on Biomedical Engineering.

[89]  Michael S. Lewicki,et al.  Efficient coding of natural sounds , 2002, Nature Neuroscience.

[90]  Emmanuel J. Candès,et al.  The curvelet transform for image denoising , 2002, IEEE Trans. Image Process..

[91]  Visa Koivunen,et al.  Blind separation methods based on Pearson system and its extensions , 2002, Signal Process..

[92]  Rémi Gribonval Sparse decomposition of stereo signals with Matching Pursuit and application to blind separation of more than two sources from a stereo mixture , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[93]  Barak A. Pearlmutter,et al.  Independent Components of Magnetoencephalography: Localization , 2002, Neural Computation.

[94]  C. Sanchez,et al.  Packet wavelet decomposition: An approach for atrial activity extraction , 2002, Computers in Cardiology.

[95]  Fabian J Theis,et al.  Formalization of the Two-Step Approach to Overcomplete BSS , 2002 .

[96]  John J. Shynk,et al.  A successive cancellation algorithm for fetal heart-rate estimation using an intrauterine ECG signal , 2002, IEEE Trans. Biomed. Eng..

[97]  Barak A. Pearlmutter,et al.  Independent Components of Magnetoencephalography: Single-Trial Response Onset Times , 2002, NeuroImage.

[98]  Bruno Torrésani,et al.  Hybrid representations for audiophonic signal encoding , 2002, Signal Process..

[99]  Arie Yeredor,et al.  Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation , 2002, IEEE Trans. Signal Process..

[100]  Christopher J. James,et al.  Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis , 2003, IEEE Transactions on Biomedical Engineering.

[101]  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.

[102]  César Sánchez,et al.  ICA APPLIED TO ATRIAL FIBRILLATION ANALYSIS , 2003 .

[103]  R. Gribonval,et al.  Proposals for Performance Measurement in Source Separation , 2003 .

[104]  Robert D. Nowak,et al.  An EM algorithm for wavelet-based image restoration , 2003, IEEE Trans. Image Process..

[105]  Yehoshua Y. Zeevi,et al.  A Multiscale Framework For Blind Separation of Linearly Mixed Signals , 2003, J. Mach. Learn. Res..

[106]  Remi Gribonval Piecewise linear source separation , 2003, SPIE Optics + Photonics.

[107]  I. Daubechies,et al.  An iterative thresholding algorithm for linear inverse problems with a sparsity constraint , 2003, math/0307152.

[108]  Fabian J. Theis,et al.  Linear Geometric ICA: Fundamentals and Algorithms , 2003, Neural Computation.

[109]  E. Oja,et al.  Blind decomposition of multimodal evoked responses and DC fields , 2003 .

[110]  M. Zibulevsky BLIND SOURCE SEPARATION WITH RELATIVE NEWTON METHOD , 2003 .

[111]  Yannick Deville,et al.  Blind separation of dependent sources using the "time-frequency ratio of mixtures" approach , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[112]  Jean-Luc Starck,et al.  Image decomposition: separation of texture from piecewise smooth content , 2003, SPIE Optics + Photonics.

[113]  Fabian J. Theis,et al.  A HISTOGRAM-BASED OVERCOMPLETE ICA ALGORITHM , 2003 .

[114]  M. Chung Current clinical issues in atrial fibrillation. , 2003, Cleveland Clinic journal of medicine.

[115]  Vince D. Calhoun,et al.  ICA of functional MRI data: an overview. , 2003 .

[116]  S. Baillet,et al.  Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering , 2004, Clinical Neurophysiology.

[117]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.

[118]  Ben H. Jansen,et al.  Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns , 1995, Biological Cybernetics.

[119]  José Millet-Roig,et al.  Atrial activity extraction for atrial fibrillation analysis using blind source separation , 2004, IEEE Transactions on Biomedical Engineering.

[120]  Joel A. Tropp,et al.  Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.

[121]  Alexander M. Bronstein,et al.  Blind source separation using block-coordinate relative Newton method , 2004, Signal Process..

[122]  Rémi Gribonval,et al.  On the Strong Uniqueness of Highly Sparse Representations from Redundant Dictionaries , 2004, ICA.

[123]  Cédric Févotte,et al.  Two contributions to blind source separation using time-frequency distributions , 2004, IEEE Signal Processing Letters.

[124]  C. Joyce,et al.  Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. , 2004, Psychophysiology.

[125]  Scott Rickard,et al.  Blind separation of speech mixtures via time-frequency masking , 2004, IEEE Transactions on Signal Processing.

[126]  Lucas C. Parra,et al.  Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain , 2004, IEEE Transactions on Medical Imaging.

[127]  Dario Farina,et al.  Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals , 2004, IEEE Transactions on Biomedical Engineering.

[128]  Bhaskar D. Rao,et al.  Sparse solutions to linear inverse problems with multiple measurement vectors , 2005, IEEE Transactions on Signal Processing.

[129]  Pierre Vandergheynst,et al.  A simple test to check the optimality of sparse signal approximations , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[130]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[131]  Y. Deville,et al.  Time–frequency ratio-based blind separation methods for attenuated and time-delayed sources , 2005 .

[132]  J. Pulkkinen,et al.  Independent component analysis to proton spectroscopic imaging data of human brain tumours. , 2005, European journal of radiology.

[133]  Charles Dossal Estimation de fonctions géométriques et déconvolution , 2005 .

[134]  Pablo Laguna,et al.  Bioelectrical Signal Processing in Cardiac and Neurological Applications , 2005 .

[135]  R. Guevara,et al.  What Can We Really Say About Neuronal Synchrony? , 2005 .

[136]  Arnaud Delorme,et al.  Frontal midline EEG dynamics during working memory , 2005, NeuroImage.

[137]  Yehoshua Y. Zeevi,et al.  Quasi Maximum Likelihood Blind Deconvolution of Images Using Optimal Sparse Representations , 2003 .

[138]  José Millet-Roig,et al.  Spatiotemporal blind source separation approach to atrial activity estimation in atrial tachyarrhythmias , 2005, IEEE Transactions on Biomedical Engineering.

[139]  Lionel Tarassenko,et al.  Application of independent component analysis in removing artefacts from the electrocardiogram , 2006, Neural Computing & Applications.

[140]  Alexander M. Bronstein,et al.  Relative optimization for blind deconvolution , 2005, IEEE Transactions on Signal Processing.

[141]  J. Bobin,et al.  Morphological component analysis , 2005, SPIE Optics + Photonics.

[142]  Yannick Deville,et al.  A time-frequency blind signal separation method applicable to underdetermined mixtures of dependent sources , 2005, Signal Process..

[143]  UNDERDETERMINED SPARSE BLIND SOURCE SEPARATION WITH DELAYS , 2005 .

[144]  Herbert Bauer,et al.  Using ICA for removal of ocular artifacts in EEG recorded from blind subjects , 2005, Neural Networks.

[145]  J. Fuchs SOME FURTHER RESULTS ON THE RECOVERY ALGORITHMS , 2005 .

[146]  Laurent Albera,et al.  Fourth-order blind identification of underdetermined mixtures of sources (FOBIUM) , 2005, IEEE Transactions on Signal Processing.

[147]  Berwin A. Turlach,et al.  On algorithms for solving least squares problems under an L1 penalty or an L1 constraint , 2005 .

[148]  A. Engel,et al.  What is novel in the novelty oddball paradigm? Functional significance of the novelty P3 event-related potential as revealed by independent component analysis. , 2005, Brain research. Cognitive brain research.

[149]  Dmitry M. Malioutov,et al.  Homotopy continuation for sparse signal representation , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[150]  A. Bruckstein,et al.  K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .

[151]  Pascal Frossard,et al.  Flexible motion-adaptive video coding with redundant expansions , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[152]  Lotfi Senhadji,et al.  Blind source separation for ambulatory sleep recording , 2006, IEEE Transactions on Information Technology in Biomedicine.

[153]  Simon J. Godsill,et al.  A Bayesian Approach for Blind Separation of Sparse Sources , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[154]  Pierre Vandergheynst,et al.  A simple test to check the optimality of a sparse signal approximation , 2006, Signal Process..

[155]  Pascal Frossard,et al.  Low-rate and flexible image coding with redundant representations , 2006, IEEE Transactions on Image Processing.

[156]  Michael Elad,et al.  Why Simple Shrinkage Is Still Relevant for Redundant Representations? , 2006, IEEE Transactions on Information Theory.

[157]  J. Tropp Algorithms for simultaneous sparse approximation. Part II: Convex relaxation , 2006, Signal Process..

[158]  Michael Elad,et al.  Stable recovery of sparse overcomplete representations in the presence of noise , 2006, IEEE Transactions on Information Theory.

[159]  Dany Leviatan,et al.  Simultaneous approximation by greedy algorithms , 2006, Adv. Comput. Math..

[160]  Pierre Vandergheynst,et al.  Image compression using an edge adapted redundant dictionary and wavelets , 2006, Signal Process..

[161]  M. Elad,et al.  $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.

[162]  Rémi Gribonval,et al.  A Robust Method to Count and Locate Audio Sources in a Stereophonic Linear Instantaneous Mixture , 2006, ICA.

[163]  Joel A. Tropp,et al.  ALGORITHMS FOR SIMULTANEOUS SPARSE APPROXIMATION , 2006 .

[164]  Sacha Krstulovic,et al.  Under-Determined Source Separation: Comparison of Two Approaches Based on Sparse Decompositions , 2006, ICA.

[165]  Joel A. Tropp,et al.  Just relax: convex programming methods for identifying sparse signals in noise , 2006, IEEE Transactions on Information Theory.

[166]  Pierre Vandergheynst,et al.  On the exponential convergence of matching pursuits in quasi-incoherent dictionaries , 2006, IEEE Transactions on Information Theory.

[167]  Sacha Krstulovic,et al.  Mptk: Matching Pursuit Made Tractable , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[168]  A. Bruckstein,et al.  On the uniqueness of overcomplete dictionaries, and a practical way to retrieve them , 2006 .

[169]  Joel A. Tropp,et al.  Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit , 2006, Signal Process..

[170]  Michael Zibulevsky,et al.  Relative Newton and Smoothing Multiplier Optimization Methods for Blind Source Separation , 2007, Blind Speech Separation.

[171]  Mohamed-Jalal Fadili,et al.  Morphological Component Analysis: An Adaptive Thresholding Strategy , 2007, IEEE Transactions on Image Processing.

[172]  Steven J. Schiff,et al.  Dangerous phase , 2007, Neuroinformatics.

[173]  R. Gribonval,et al.  Highly sparse representations from dictionaries are unique and independent of the sparseness measure , 2007 .

[174]  Sanqing Hu,et al.  Automatic Identification and Removal of Scalp Reference Signal for Intracranial EEGs Based on Independent Component Analysis , 2007, IEEE Transactions on Biomedical Engineering.

[175]  Pierre Comon,et al.  Comparative Speed Analysis of FastICA , 2007, ICA.

[176]  Emmanuel Vincent,et al.  Complex Nonconvex l p Norm Minimization for Underdetermined Source Separation , 2007, ICA.

[177]  Michael Elad,et al.  Coordinate and subspace optimization methods for linear least squares with non-quadratic regularization , 2007 .

[178]  H. K. Verma,et al.  Artifacts and noise removal in electrocardiograms using independent component analysis. , 2008, International journal of cardiology.

[179]  H. Rauhut,et al.  Atoms of All Channels, Unite! Average Case Analysis of Multi-Channel Sparse Recovery Using Greedy Algorithms , 2008 .

[180]  Massimo Fornasier,et al.  Recovery Algorithms for Vector-Valued Data with Joint Sparsity Constraints , 2008, SIAM J. Numer. Anal..

[181]  Christian Jutten,et al.  On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics , 2008, Clinical Neurophysiology.

[182]  Reza Sameni,et al.  Extraction of Fetal Cardiac Signals from an Array of Maternal Abdominal Recordings , 2008 .

[183]  P. Comon,et al.  Ica: a potential tool for bci systems , 2008, IEEE Signal Processing Magazine.

[184]  E. Oja,et al.  BSS and ICA in Neuroinformatics: From Current Practices to Open Challenges , 2008, IEEE Reviews in Biomedical Engineering.

[185]  Lieven De Lathauwer,et al.  Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization , 2008, IEEE Transactions on Signal Processing.

[186]  Pierre Comon,et al.  Robust independent component analysis for blind source separation and extraction with application in electrocardiography , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[187]  Morten Nielsen,et al.  Beyond sparsity: Recovering structured representations by ${\ell}^1$ minimization and greedy algorithms , 2007, Adv. Comput. Math..

[188]  Lotfi Senhadji,et al.  Chapter 18 – Biomedical applications , 2010 .

[189]  Deanna Needell,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.

[190]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.