Blind Separation of Noisy Image Mixtures
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[1] S Makeig,et al. Spatially independent activity patterns in functional MRI data during the stroop color-naming task. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[2] Schuster,et al. Separation of a mixture of independent signals using time delayed correlations. , 1994, Physical review letters.
[3] Elie Bienenstock,et al. Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.
[4] Lars Kai Hansen,et al. Revisiting Boltzmann learning: parameter estimation in Markov random fields , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[5] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[6] Andrzej Cichocki,et al. A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.
[7] Lars Kai Hansen,et al. Visualization of neural networks using saliency maps , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.
[8] H. Attias,et al. Blind source separation and deconvolution by dynamic component analysis , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.
[9] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[10] J R Moeller,et al. A Regional Covariance Approach to the Analysis of Functional Patterns in Positron Emission Tomographic Data , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[11] Eric Moulines,et al. Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[12] Barak A. Pearlmutter,et al. A Context-Sensitive Generalization of ICA , 1996 .
[13] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[14] Terrence J. Sejnowski,et al. Learning Overcomplete Representations , 2000, Neural Computation.
[15] Lars Kai Hansen,et al. Unsupervised learning and generalization , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).
[16] Geoffrey E. Hinton,et al. Learning and relearning in Boltzmann machines , 1986 .
[17] Te-Won Lee,et al. Independent Component Analysis , 1998, Springer US.
[18] B. Olshausen. Learning linear, sparse, factorial codes , 1996 .
[19] L. K. Hansen,et al. Generalizable Patterns in Neuroimaging: How Many Principal Components? , 1999, NeuroImage.
[20] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[21] Carsten Peterson,et al. A Mean Field Theory Learning Algorithm for Neural Networks , 1987, Complex Syst..
[22] Lars Kai Hansen,et al. Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover , 1997, IPMI.