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ICASSP
2010
IEEE
15 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
15 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...
135
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ICA
2004
Springer
15 years 9 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
15 years 4 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
15 years 9 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