| Autor: |
Jun Wang, Xiaofeng Liao, Zhang Yi, Hailin Liu, Yiuming Cheung |
| Zdroj: |
Advances in Neural Networks - ISNN 2005 (9783540259138); 2005, p472-477, 6p |
| Abstrakt: |
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 un-mixing matrix directly works out from the GE equation without time-consuming 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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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