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» ICA for Noisy Neurobiological Data
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ICA
2007
Springer
13 years 10 months ago
Morphological Diversity and Sparsity in Blind Source Separation
This paper describes a new blind source separation method for instantaneous linear mixtures. This new method coined GMCA (Generalized Morphological Component Analysis) relies on mo...
Jérôme Bobin, Yassir Moudden, Jalal F...
IJON
2006
169views more  IJON 2006»
13 years 4 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...