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ICASSP
2010
IEEE
13 years 3 months ago
Independent subspace analysis with prior information for fMRI data
Independent component analysis (ICA) has been successfully applied for the analysis of functional magnetic resonance imaging (fMRI) data. However, independence might be too strong...
Sai Ma, Xi-Lin Li, Nicolle M. Correa, Tülay A...
IJON
2006
72views more  IJON 2006»
13 years 4 months ago
Extraction of a source signal whose kurtosis value lies in a specific range
In many applications extraction of source signals of interest from observed signals maybe is a more feasible approach than simultaneous separation of all the source signals, since...
Zhi-Lin Zhang, Zhang Yi
ICA
2007
Springer
13 years 11 months ago
Subspaces of Spatially Varying Independent Components in fMRI
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
Jarkko Ylipaavalniemi, Ricardo Vigário
ICML
2009
IEEE
13 years 11 months ago
Grammatical inference as a principal component analysis problem
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Raphaël Bailly, François Denis, Liva R...
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...