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11

ISNN
2005
Springer

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A Learning Framework for Blind Source Separation Using Generalized Eigenvalues

13 years 10 months ago

A Learning Framework for Blind Source Separation Using Generalized Eigenvalues

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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

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Blind Source Separation | ISNN 2005 | Typical Information-theoretical Approaches | Unknown Unmixing Matrix |

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Added	27 Jun 2010
Updated	27 Jun 2010
Type	Conference
Year	2005
Where	ISNN
Authors	Hailin Liu, Yiu-ming Cheung

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