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ICA
2004
Springer
14 years 2 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
ICASSP
2011
IEEE
13 years 9 days ago
Global convergence of independent component analysis based on semidefinite programming relaxation
In the independent component analysis, polynomial functions of higher order statistics are often used as cost functions. However, such cost functions usually have many local minim...
Shotaro Akaho, Jun Fujiki
ICASSP
2011
IEEE
13 years 9 days ago
A novel vector quantization-based video summarization method using independent component analysis mixture model
In this paper, we present a new independent component analysis mixture vector quantization (ICAMVQ) method to summarize the video content. In particular, independent component ana...
Junfeng Jiang, Xiao-Ping Zhang
ICA
2007
Springer
14 years 2 months ago
Optimization on the Orthogonal Group for Independent Component Analysis
Abstract. This paper derives a new algorithm that performs independent component analysis (ICA) by optimizing the contrast function of the RADICAL algorithm. The core idea of the p...
Michel Journée, Pierre-Antoine Absil, Rodol...
NN
2000
Springer
177views Neural Networks» more  NN 2000»
13 years 8 months ago
Independent component analysis: algorithms and applications
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
Aapo Hyvärinen, Erkki Oja