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ESANN
2006
10 years 11 months ago
Semi-Blind Approaches for Source Separation and Independent component Analysis
Abstract. This paper is a survey of semi-blind source separation approaches. Since Gaussian iid signals are not separable, simplest priors suggest to assume non Gaussian iid signal...
Massoud Babaie-Zadeh, Christian Jutten
NN
2000
Springer
159views Neural Networks» more  NN 2000»
10 years 10 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
NIPS
2004
10 years 11 months ago
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unkno...
Tobias Blaschke, Laurenz Wiskott
ICASSP
2010
IEEE
10 years 8 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...
ICA
2004
Springer
11 years 3 months ago
Independent Slow Feature Analysis and Nonlinear Blind Source Separation
We present independent slow feature analysis as a new method for nonlinear blind source separation. It circumvents the indeterminacy of nonlinear independent component analysis by ...
Tobias Blaschke, Laurenz Wiskott
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