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» A Constraint Learning Algorithm for Blind Source Separation
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ICASSP
2009
IEEE
13 years 5 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...
ISCAS
2006
IEEE
102views Hardware» more  ISCAS 2006»
14 years 1 months ago
Eigenvector algorithms using reference signals for blind source separation of instantaneous mixtures
— This paper presents an eigenvector algorithm (EVA) derived from a criterion using reference signals, in which the EVA is applied to the blind source separation (BSS) of instant...
Mitsuru Kawamoto, Kiyotaka Kohno, Yujiro Inouye
ESANN
2003
13 years 9 months ago
Comparison of neural algorithms for blind source separation in sensor array applications
- A test bed of experiments with real and artificially generated data has been designed to compare the performance of three well-known algorithms for BSS. The main goal of these ex...
Guillermo Bedoya, Sergio Bermejo, Joan Cabestany
ICASSP
2008
IEEE
14 years 2 months ago
Extension of EFICA algorithm for blind separation of piecewise stationary non Gaussian sources
We propose an extension of EFICA algorithm for piecewise stationary and non Gaussian signals. The proposed method is able to profit from varying distribution of the original sign...
Zbynek Koldovský, Jirí Málek,...
NIPS
2004
13 years 9 months ago
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unkno...
Tobias Blaschke, Laurenz Wiskott