Blind Source Separation Exploiting Higher-Order Frequency Dependencies
暂无分享,去创建一个
Te-Won Lee | Soo-Young Lee | Hagai Attias | Taesu Kim | H. Attias | Soo-Young Lee | Te-Won Lee | Taesu Kim
[1] R. Stephens,et al. Acoustics and Vibrational Physics , 1966 .
[2] Jont B. Allen,et al. Image method for efficiently simulating small‐room acoustics , 1976 .
[3] William G. Gardner,et al. The virtual acoustic room , 1992 .
[4] Andrzej Cichocki,et al. A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.
[5] Kari Torkkola,et al. Blind separation of convolved sources based on information maximization , 1996, Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop.
[6] R. Lambert. Multichannel blind deconvolution: FIR matrix algebra and separation of multipath mixtures , 1996 .
[7] Te-Won Lee,et al. Blind Separation of Delayed and Convolved Sources , 1996, NIPS.
[8] Ehud Weinstein,et al. Multichannel signal separation: methods and analysis , 1996, IEEE Trans. Signal Process..
[9] Te-Won Lee,et al. Independent Component Analysis , 1998, Springer US.
[10] 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).
[11] Stephan Weiss,et al. On adaptive filtering in oversampled subbands , 1998 .
[12] Paris Smaragdis,et al. Blind separation of convolved mixtures in the frequency domain , 1998, Neurocomputing.
[13] Kazuya Takeda,et al. Evaluation of blind signal separation method using directivity pattern under reverberant conditions , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[14] Birger Kollmeier,et al. Amplitude Modulation Decorrelation For Convolutive Blind Source Separation , 2000 .
[15] Terrence J. Sejnowski,et al. ICA Mixture Models for Unsupervised Classification of Non-Gaussian Classes and Automatic Context Switching in Blind Signal Separation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[16] Lucas C. Parra,et al. Convolutive blind separation of non-stationary sources , 2000, IEEE Trans. Speech Audio Process..
[17] Aapo Hyvärinen,et al. Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces , 2000, Neural Computation.
[18] B. Kollmeier,et al. Convolutive blind source separation of speech signals based on amplitude modulation decorrelation , 2000 .
[19] Andreas Ziehe,et al. An approach to blind source separation based on temporal structure of speech signals , 2001, Neurocomputing.
[20] Aapo Hyvärinen,et al. Topographic Independent Component Analysis , 2001, Neural Computation.
[21] Dennis R. Morgan,et al. A beamforming approach to permutation alignment for multichannel frequency-domain blind speech separation , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[22] Michael S. Lewicki,et al. Unsupervised image classification, segmentation, and enhancement using ICA mixture models , 2002, IEEE Trans. Image Process..
[23] K. Matsuoka,et al. Minimal distortion principle for blind source separation , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..
[24] Nobuhiko Kitawaki,et al. Combined approach of array processing and independent component analysis for blind separation of acoustic signals , 2003, IEEE Trans. Speech Audio Process..
[25] William S. Rayens,et al. Independent Component Analysis: Principles and Practice , 2003, Technometrics.
[26] M. Lewicki,et al. Learning higher-order structures in natural images , 2003, Network.
[27] Hiroshi Sawada,et al. A robust and precise method for solving the permutation problem of frequency-domain blind source separation , 2004, IEEE Transactions on Speech and Audio Processing.
[28] Te-Won Lee,et al. Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution , 2004, NIPS.