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» A sparse component model of source signals and its applicati...
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ICML
2007
IEEE
14 years 8 months ago
Nonlinear independent component analysis with minimal nonlinear distortion
Nonlinear ICA may not result in nonlinear blind source separation, since solutions to nonlinear ICA are highly non-unique. In practice, the nonlinearity in the data generation pro...
Kun Zhang, Laiwan Chan
CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 7 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
ICASSP
2010
IEEE
13 years 7 months ago
Gradient Polytope Faces Pursuit for large scale sparse recovery problems
Polytope Faces Pursuit is a greedy algorithm that performs Basis Pursuit with similar order complexity to Orthogonal Matching Pursuit. The algorithm adds one basis vector at a tim...
Aris Gretsistas, Ivan Damnjanovic, Mark D. Plumble...
IJON
2006
169views more  IJON 2006»
13 years 7 months ago
Denoising using local projective subspace methods
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
Peter Gruber, Kurt Stadlthanner, Matthias Böh...
NIPS
1997
13 years 8 months ago
Extended ICA Removes Artifacts from Electroencephalographic Recordings
Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, muscle, heart and line noise is a serious problem for EEG interpretation and analysis. Rej...
Tzyy-Ping Jung, Colin Humphries, Te-Won Lee, Scott...