Behavioral / Systems / Cognitive Sparse Representations for the Cocktail Party Problem
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[1] Anat Levin,et al. User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Barak A. Pearlmutter,et al. Sparse Representations for the Cocktail Party Problem , 2006, The Journal of Neuroscience.
[3] Michael S. Lewicki,et al. Efficient auditory coding , 2006, Nature.
[4] T. Hromádka,et al. Reliability and Representational Bandwidth in the Auditory Cortex , 2005, Neuron.
[5] J. Rauschecker,et al. Perceptual Organization of Tone Sequences in the Auditory Cortex of Awake Macaques , 2005, Neuron.
[6] Paris Smaragdis,et al. Non-negative Matrix Factor Deconvolution; Extraction of Multiple Sound Sources from Monophonic Inputs , 2004, ICA.
[7] J. Arezzo,et al. Auditory stream segregation in monkey auditory cortex: effects of frequency separation, presentation rate, and tone duration. , 2004, The Journal of the Acoustical Society of America.
[8] J. Gallant,et al. Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons , 2004, The Journal of Neuroscience.
[9] Bruno A Olshausen,et al. Sparse coding of sensory inputs , 2004, Current Opinion in Neurobiology.
[10] Yuanqing Li,et al. Analysis of Sparse Representation and Blind Source Separation , 2004, Neural Computation.
[11] Christian K. Machens,et al. Linearity of Cortical Receptive Fields Measured with Natural Sounds , 2004, The Journal of Neuroscience.
[12] Jonathan Z. Simon,et al. Robust Spectrotemporal Reverse Correlation for the Auditory System: Optimizing Stimulus Design , 2000, Journal of Computational Neuroscience.
[13] Masakazu Konishi,et al. Mechanisms of sound localization in the barn owl (Tyto alba) , 1979, Journal of comparative physiology.
[14] Christoph E Schreiner,et al. Spectrotemporal structure of receptive fields in areas AI and AAF of mouse auditory cortex. , 2003, Journal of neurophysiology.
[15] Terrence J Sejnowski,et al. Communication in Neuronal Networks , 2003, Science.
[16] M. DeWeese,et al. Binary Spiking in Auditory Cortex , 2003, The Journal of Neuroscience.
[17] Xiaoqin Wang,et al. Auditory Cortical Responses Elicited in Awake Primates by Random Spectrum Stimuli , 2003, The Journal of Neuroscience.
[18] Joseph F. Murray,et al. Dictionary Learning Algorithms for Sparse Representation , 2003, Neural Computation.
[19] Konrad P. Körding,et al. Sparse Spectrotemporal Coding of Sounds , 2003, EURASIP J. Adv. Signal Process..
[20] Michael S. Lewicki,et al. Efficient coding of natural sounds , 2002, Nature Neuroscience.
[21] Bruno A. Olshausen,et al. A new window on sound , 2002, Nature Neuroscience.
[22] Paul M. Hofman,et al. Bayesian reconstruction of sound localization cues from responses to random spectra , 2002, Biological Cybernetics.
[23] R. Linsker. Separation of a mixture of acoustic sources into its components , 2002 .
[24] K. D. Punta,et al. An ultra-sparse code underlies the generation of neural sequences in a songbird , 2002 .
[25] D. Donoho,et al. Maximal Sparsity Representation via l 1 Minimization , 2002 .
[26] Michael Zibulevsky,et al. Underdetermined blind source separation using sparse representations , 2001, Signal Process..
[27] Eero P. Simoncelli,et al. Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.
[28] Barak A. Pearlmutter,et al. Blind Source Separation by Sparse Decomposition in a Signal Dictionary , 2001, Neural Computation.
[29] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[30] J. Gallant,et al. Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. , 2001, Network.
[31] Michael C. Mozer,et al. Monaural Separation and Classification of Mixed Signals : a Support-vector Regression Perspective , 2001 .
[32] Tomaso Poggio,et al. Models of object recognition , 2000, Nature Neuroscience.
[33] S. Rickard,et al. DOA estimation of many W-disjoint orthogonal sources from two mixtures using DUET , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).
[34] M. Sutter. Shapes and level tolerances of frequency tuning curves in primary auditory cortex: quantitative measures and population codes. , 2000, Journal of neurophysiology.
[35] K. Sen,et al. Spectral-temporal Receptive Fields of Nonlinear Auditory Neurons Obtained Using Natural Sounds , 2022 .
[36] J L Gallant,et al. Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.
[37] Terrence J. Sejnowski,et al. Learning Overcomplete Representations , 2000, Neural Computation.
[38] Kazuya Takeda,et al. Estimating Head Related Transfer Function Using Multiple Regression Analysis , 2000 .
[39] Sam T. Roweis,et al. One Microphone Source Separation , 2000, NIPS.
[40] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[41] H Farid,et al. Separating reflections from images by use of independent component analysis. , 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.
[42] Gert Cauwenberghs,et al. Monaural separation of independent acoustical components , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).
[43] Terrence J. Sejnowski,et al. Blind source separation of more sources than mixtures using overcomplete representations , 1999, IEEE Signal Processing Letters.
[44] Israel Nelken,et al. Responses of auditory-cortex neurons to structural features of natural sounds , 1999, Nature.
[45] H. Steven Colburn,et al. Role of spectral detail in sound-source localization , 1998, Nature.
[46] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[47] Shun-ichi Amari,et al. Adaptive blind signal processing-neural network approaches , 1998, Proc. IEEE.
[48] M. Merzenich,et al. Optimizing sound features for cortical neurons. , 1998, Science.
[49] L. Abbott,et al. Responses of neurons in primary and inferior temporal visual cortices to natural scenes , 1997, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[50] David J. Field,et al. Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.
[51] Terrence J. Sejnowski,et al. The “independent components” of natural scenes are edge filters , 1997, Vision Research.
[52] I. Nelken. Demonstrations of Auditory Scene Analysis: The Perceptual Organization of Sound by Albert S. Bregman and Pierre A. Ahad, MIT Press, 1996. £15.95 CD , 1997, Trends in Neurosciences.
[53] Hagai Attias,et al. Temporal Low-Order Statistics of Natural Sounds , 1996, NIPS.
[54] S. Shamma,et al. Analysis of dynamic spectra in ferret primary auditory cortex. II. Prediction of unit responses to arbitrary dynamic spectra. , 1996, Journal of neurophysiology.
[55] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[56] William B. Levy,et al. Energy Efficient Neural Codes , 1996, Neural Computation.
[57] S. Sheft,et al. A simulated “cocktail party” with up to three sound sources , 1996, Perception & psychophysics.
[58] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[59] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[60] F L Wightman,et al. Localization using nonindividualized head-related transfer functions. , 1993, The Journal of the Acoustical Society of America.
[61] Pierre Comon,et al. Blind separation of sources, part II: Problems statement , 1991, Signal Process..
[62] William Bialek,et al. Reading a Neural Code , 1991, NIPS.
[63] F L Wightman,et al. Headphone simulation of free-field listening. II: Psychophysical validation. , 1989, The Journal of the Acoustical Society of America.
[64] Tomaso Poggio,et al. Computational vision and regularization theory , 1985, Nature.
[65] R. Fletcher. Semi-Definite Matrix Constraints in Optimization , 1985 .