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ISNN
2005
Springer

A Learning Framework for Blind Source Separation Using Generalized Eigenvalues

8 years 11 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 information-theoretical approaches, this new one has at least two merits: (1) the unknown unmixing matrix directly works out from the GE equation without timeconsuming iterative learning; (2) The correctness of the solution is guaranteed. We give out a general learning procedure under this framework. The computer simulation shows validity of our method.
Hailin Liu, Yiu-ming Cheung
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ISNN
Authors Hailin Liu, Yiu-ming Cheung
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