TY - JOUR
T1 - On blind source separation using generalized eigenvalues with a new metric
AU - Liu, Hai lin
AU - CHEUNG, Yiu Ming
N1 - Funding Information:
The work described in this paper was supported by Faculty Research Grant of Hong Kong Baptist University with Project Number: FRG/05-06/II-42, FRG/06-07/II-07, and by the Research Grant Council of Hong Kong SAR under Projects HKBU 2156/04E and HKBU 210306.
PY - 2008/1
Y1 - 2008/1
N2 - Following the seminal work of Stone [Independent Component Analysis, The MIT Press, Cambridge, 2004], this paper presents a new metric for blind source separation (BSS). It is proved that the metric value of any linear combination of source signals is less than the largest one of sources under a loose condition. Further, the global optimization of this new metric is achieved by formulating it as a generalized eigenvalue (GE) problem. Subsequently, we give out a fast BSS algorithm. Moreover, we analyze the solution properties of ill-posed BSS, and further show that the proposed algorithm is applicable to such a case as well. The numerical simulations demonstrate the efficacy of our algorithm.
AB - Following the seminal work of Stone [Independent Component Analysis, The MIT Press, Cambridge, 2004], this paper presents a new metric for blind source separation (BSS). It is proved that the metric value of any linear combination of source signals is less than the largest one of sources under a loose condition. Further, the global optimization of this new metric is achieved by formulating it as a generalized eigenvalue (GE) problem. Subsequently, we give out a fast BSS algorithm. Moreover, we analyze the solution properties of ill-posed BSS, and further show that the proposed algorithm is applicable to such a case as well. The numerical simulations demonstrate the efficacy of our algorithm.
KW - Blind source separation
KW - Generalized eigenvalue problem
KW - Ill-posed ICA
KW - Independent component analysis
KW - Optimal solution
UR - http://www.scopus.com/inward/record.url?scp=38649117322&partnerID=8YFLogxK
U2 - 10.1016/j.neucom.2007.02.004
DO - 10.1016/j.neucom.2007.02.004
M3 - Journal article
AN - SCOPUS:38649117322
SN - 0925-2312
VL - 71
SP - 973
EP - 982
JO - Neurocomputing
JF - Neurocomputing
IS - 4-6
ER -