DocumentCode :
2975209
Title :
ICA algorithms for 3 sources and 2 sensors
Author :
De Lathauwer, L. ; Comon, P. ; De Moor, B. ; Vandewalle, J.
Author_Institution :
ESAT, Katholieke Univ., Leuven, Heverlee, Belgium
fYear :
1999
fDate :
1999
Firstpage :
116
Lastpage :
120
Abstract :
In this paper we develop efficient algorithms to identify the mixing matrix in the context of an independent component analysis with 3 sources and 2 sensors. Our contribution is two-fold. First, by applying twice a theorem by Sylvester, it is shown that the mixture can be obtained analytically by solving a linear system involving cumulants of both orders 3 and 4. Secondly, the latter theorem is extended to the case of “polynomials” of complex variables in which each monomial counts the same number of complex conjugated unknowns; this leads to an algorithm allowing us to identify the mixture by solving a linear system involving only 4th-order cumulants
Keywords :
higher order statistics; identification; matrix algebra; polynomials; signal processing; 4th-order cumulants; ICA algorithms; blind source separation; complex conjugated unknowns; complex variable polynomials; independent component analysis; linear system; mixing matrix identification; monomial; sensors; Algorithm design and analysis; Biosensors; Computational efficiency; Ear; Image reconstruction; Independent component analysis; Linear systems; Mobile communication; Tellurium; Tensile stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Caesarea
Print_ISBN :
0-7695-0140-0
Type :
conf
DOI :
10.1109/HOST.1999.778706
Filename :
778706
Link To Document :
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