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ESANN
2004
13 years 5 months ago
Linearization identification and an application to BSS using a SOM
The one-dimensional functional equation g(y(t)) = cg(z(t)) with known functions y and z and constant c is considered. The indeterminacies are calculated, and an algorithm for appro...
Fabian J. Theis, Elmar Wolfgang Lang
ICASSP
2009
IEEE
13 years 2 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
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...
DSP
2007
13 years 4 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
TASLP
2010
138views more  TASLP 2010»
12 years 11 months ago
Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...