K-hyperline clustering learning for sparse component analysis
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Yuanqing Li | Zhaoshui He | Andrzej Cichocki | Shengli Xie | Saeid Sanei | A. Cichocki | S. Xie | Yuanqing Li | Zhaoshui He | S. Sanei
[1] Scott Rickard,et al. Blind separation of speech mixtures via time-frequency masking , 2004, IEEE Transactions on Signal Processing.
[2] Joseph F. Murray,et al. Dictionary Learning Algorithms for Sparse Representation , 2003, Neural Computation.
[3] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[4] Zhaoshui He,et al. Sparse representation and blind source separation of ill-posed mixtures , 2006, Science in China Series F: Information Sciences.
[5] Daniel W. C. Ho,et al. Underdetermined blind source separation based on sparse representation , 2006, IEEE Transactions on Signal Processing.
[6] Andrzej Cichocki,et al. Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications , 2002 .
[7] P. Laguna,et al. Signal Processing , 2002, Yearbook of Medical Informatics.
[8] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[9] Terrence J. Sejnowski,et al. Learning Overcomplete Representations , 2000, Neural Computation.
[10] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[11] Zhaoshui He,et al. K-EVD Clustering and Its Applications to Sparse Component Analysis , 2006, ICA.
[12] Michael Zibulevsky,et al. Underdetermined blind source separation using sparse representations , 2001, Signal Process..
[13] Rémi Gribonval,et al. A Robust Method to Count and Locate Audio Sources in a Stereophonic Linear Instantaneous Mixture , 2006, ICA.
[14] 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.
[15] Christian Jutten,et al. Sparse ICA via cluster-wise PCA , 2006, Neurocomputing.
[16] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[17] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[18] Mark A. Girolami,et al. A Variational Method for Learning Sparse and Overcomplete Representations , 2001, Neural Computation.
[19] Fabian J. Theis,et al. Median-based clustering for underdetermined blind signal processing , 2006, IEEE Signal Processing Letters.
[20] Maurice K. Wong,et al. Algorithm AS136: A k-means clustering algorithm. , 1979 .
[21] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[22] A. Cichocki,et al. Multilayer nonnegative matrix factorisation , 2006 .
[23] Liqing Zhang,et al. A Note on Lewicki-Sejnowski Gradient for Learning Overcomplete Representations , 2008, Neural Computation.
[24] D. Donoho,et al. Maximal Sparsity Representation via l 1 Minimization , 2002 .
[25] Terrence J. Sejnowski,et al. Blind source separation of more sources than mixtures using overcomplete representations , 1999, IEEE Signal Processing Letters.
[26] Yuanqing Li,et al. Analysis of Sparse Representation and Blind Source Separation , 2004, Neural Computation.
[27] A. Bruckstein,et al. K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .
[28] Andrew W. Moore,et al. Detecting Significant Multidimensional Spatial Clusters , 2004, NIPS.
[29] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[30] G. McLachlan,et al. The EM algorithm and extensions , 1996 .
[31] Mineichi Kudo,et al. Performance analysis of minimum /spl lscr//sub 1/-norm solutions for underdetermined source separation , 2004, IEEE Transactions on Signal Processing.
[32] Bhaskar D. Rao,et al. Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm , 1997, IEEE Trans. Signal Process..
[33] Barak A. Pearlmutter,et al. Blind Source Separation by Sparse Decomposition in a Signal Dictionary , 2001, Neural Computation.
[34] Michael Elad,et al. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[35] Zhaoshui He,et al. Convolutive Blind Source Separation in the Frequency Domain Based on Sparse Representation , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[36] Xie Shengli,et al. Sparse representation and blind source separation of ill-posed mixtures , 2006 .
[37] Barak A. Pearlmutter,et al. Soft-LOST: EM on a Mixture of Oriented Lines , 2004, ICA.
[38] Barak A. Pearlmutter,et al. Blind source separation by sparse decomposition , 2000, SPIE Defense + Commercial Sensing.
[39] Fabian J. Theis,et al. Linear Geometric ICA: Fundamentals and Algorithms , 2003, Neural Computation.
[40] 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).
[41] Yannick Deville,et al. A time-frequency blind signal separation method applicable to underdetermined mixtures of dependent sources , 2005, Signal Process..
[42] Bhaskar D. Rao,et al. Sparse solutions to linear inverse problems with multiple measurement vectors , 2005, IEEE Transactions on Signal Processing.