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» Learned parametric mixture based ICA algorithm
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PAMI
2006
215views more  PAMI 2006»
13 years 8 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
IJON
2006
131views more  IJON 2006»
13 years 8 months ago
Optimizing blind source separation with guided genetic algorithms
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
J. M. Górriz, Carlos García Puntonet...
DSP
2007
13 years 8 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...
TSP
2008
116views more  TSP 2008»
13 years 8 months ago
Fast Blind Separation of Long Mixture Recordings Using Multivariate Polynomial Identification
This correspondence presents new approaches for optimizing kurtosis-based separation criteria in the case of long mixture recordings. Our methods are based on a multivariate polyno...
Johan Thomas, Yannick Deville, Shahram Hosseini
ICASSP
2011
IEEE
13 years 15 days ago
A sparsity based criterion for solving the permutation ambiguity in convolutive blind source separation
In this paper, we present a new algorithm for solving the permutation ambiguity in convolutive blind source separation. A common approach for separation of convolutive mixtures is...
Radoslaw Mazur, Alfred Mertins