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ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
14 years 1 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
TASLP
2011
13 years 2 months ago
Time-Domain Blind Separation of Audio Sources on the Basis of a Complete ICA Decomposition of an Observation Space
—Time-domain algorithms for blind separation of audio sources can be classified as being based either on a partial or complete decomposition of an observation space. The decompo...
Zbynek Koldovský, Petr Tichavský
ICASSP
2011
IEEE
12 years 11 months ago
Distributed blind source separation with an application to audio signals
A scalable blind source separation paradigm aimed at sensor networks is described. The approach facilitates an unlimited number of sensors and sources and does not require a fusio...
Yusuke Hioka, W. Bastiaan Kleijn
IJON
1998
172views more  IJON 1998»
13 years 7 months ago
Blind separation of convolved mixtures in the frequency domain
In this paper we employ information theoretic algorithms, previously used for separating instantaneous mixtures of sources, for separating convolved mixtures in the frequency doma...
Paris Smaragdis
ESANN
2006
13 years 9 months ago
Semi-Blind Approaches for Source Separation and Independent component Analysis
Abstract. This paper is a survey of semi-blind source separation approaches. Since Gaussian iid signals are not separable, simplest priors suggest to assume non Gaussian iid signal...
Massoud Babaie-Zadeh, Christian Jutten