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NECO
2011
10 years 7 months ago
Least-Squares Independent Component Analysis
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Taiji Suzuki, Masashi Sugiyama
CIS
2005
Springer
11 years 5 months ago
Two Adaptive Matching Learning Algorithms for Independent Component Analysis
Independent component analysis (ICA) has been applied in many fields of signal processing and many ICA learning algorithms have been proposed from different perspectives. However...
Jinwen Ma, Fei Ge, Dengpan Gao
ICA
2004
Springer
11 years 5 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela
NIPS
2007
11 years 1 months ago
An online Hebbian learning rule that performs Independent Component Analysis
Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but o...
Claudia Clopath, André Longtin, Wulfram Ger...
ISCAS
2008
IEEE
169views Hardware» more  ISCAS 2008»
11 years 6 months ago
Sigma-delta learning for super-resolution independent component analysis
— Many source separation algorithms fail to deliver robust performance in presence of artifacts introduced by cross-channel redundancy, non-homogeneous mixing and highdimensional...
Amin Fazel, Shantanu Chakrabartty
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