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NIPS
2003
13 years 5 months ago
Sparse Representation and Its Applications in Blind Source Separation
In this paper, sparse representation (factorization) of a data matrix is first discussed. An overcomplete basis matrix is estimated by using the K−means method. We have proved ...
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Se...
ICASSP
2010
IEEE
13 years 2 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
2007
Springer
13 years 10 months ago
Morphological Diversity and Sparsity in Blind Source Separation
This paper describes a new blind source separation method for instantaneous linear mixtures. This new method coined GMCA (Generalized Morphological Component Analysis) relies on mo...
Jérôme Bobin, Yassir Moudden, Jalal F...
ICIP
2007
IEEE
14 years 6 months ago
Blind Audiovisual Source Separation using Sparse Representations
In this work we present a method to jointly separate active audio and visual structures on a given mixture. Blind Audiovisual Source Separation is achieved exploiting the coherenc...
Anna Llagostera Casanovas, Gianluca Monaci, Pierre...
ICASSP
2008
IEEE
13 years 11 months ago
Blind separation of non-negative sources by convex analysis: Effective method using linear programming
We recently reported a criterion for blind separation of non-negative sources, using a new concept called convex analysis for mixtures of non-negative sources (CAMNS). Under some ...
Tsung-Han Chan, Wing-Kin Ma, Chong-Yung Chi, Yue W...