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» A Constraint Learning Algorithm for Blind Source Separation
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ICA
2010
Springer
13 years 8 months ago
Adaptive Underdetermined ICA for Handling an Unknown Number of Sources
Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, pre...
Andreas Sandmair, Alam Zaib, Fernando Puente Le&oa...
ICASSP
2010
IEEE
13 years 5 months ago
A sparse component model of source signals and its application to blind source separation
In this paper, we propose a new method of blind source separation (BSS) for music signals. Our method has the following characteristics: 1) the method is a combination of the spar...
Yu Kitano, Hirokazu Kameoka, Yosuke Izumi, Nobutak...
ICA
2004
Springer
14 years 1 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
ISNN
2005
Springer
14 years 1 months ago
A Learning Framework for Blind Source Separation Using Generalized Eigenvalues
This paper presents a learning framework for blind source separation (BSS), in which the BSS is formulated as generalized Eigenvalue (GE) problem. Compared to the typical informati...
Hailin Liu, Yiu-ming Cheung
ISCAS
2002
IEEE
123views Hardware» more  ISCAS 2002»
14 years 18 days ago
Blind electromagnetic source separation and localization
A blind source separation algorithm is used to estimate the mixing operator from electromagnetic emission signals through independent component analysis (ICA) technique. The mixin...
Simone Fiori, Pietro Burrascano