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ICA
2007
Springer
10 years 5 months ago
On Separation of Signal Sources Using Kernel Estimates of Probability Densities
The discussion in this paper revolves around the notion of separation problems. The latter can be thought of as a unifying concept which includes a variety of important problems in...
Oleg V. Michailovich, Douglas Wiens
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
10 years 5 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata
ICA
2004
Springer
10 years 5 months ago
ICA Using Kernel Entropy Estimation with NlogN Complexity
Abstract. Mutual information (MI) is a common criterion in independent component analysis (ICA) optimization. MI is derived from probability density functions (PDF). There are scen...
Sarit Shwartz, Michael Zibulevsky, Yoav Y. Schechn...
ICANN
2010
Springer
10 years 19 days ago
A Directional Laplacian Density for Underdetermined Audio Source Separation
In this work, a novel probability distribution is proposed to model sparse directional data. The Directional Laplacian Distribution (DLD) is a hybrid between the linear Laplacian d...
Nikolaos Mitianoudis
IJON
2006
131views more  IJON 2006»
9 years 11 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...
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