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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...
NIPS
2003
13 years 6 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...
ICA
2004
Springer
13 years 10 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
ICA
2010
Springer
13 years 5 months ago
Adaptive Segmentation and Separation of Determined Convolutive Mixtures under Dynamic Conditions
Abstract. In this paper, we propose a method for blind source separation (BSS) of convolutive audio recordings with short blocks of stationary sources, i.e. dynamically changing so...
Benedikt Loesch, Bin Yang
ICA
2004
Springer
13 years 10 months ago
Estimating Functions for Blind Separation when Sources Have Variance-Dependencies
The blind separation problem where the sources are not independent, but have variance-dependencies is discussed. Hyv¨arinen and Hurri[1] proposed an algorithm which requires no as...
Motoaki Kawanabe, Klaus-Robert Müller