TY - GEN
T1 - Blind separation of instantaneous mixtures of dependent sources
AU - Castella, Marc
AU - Comon, Pierre
PY - 2007/1/1
Y1 - 2007/1/1
N2 - This paper deals with the problem of Blind Source Separation. Contrary to the vast majority of works, we do not assume the statistical independence between the sources and explicitly consider that they are dependent. We introduce three particular models of dependent sources and show that their cumulants have interesting properties. Based on these properties, we investigate the behaviour of classical Blind Source Separation algorithms when applied to these sources: depending on the source vector, the separation may be sucessful or some additionnal indeterminacies can be identified.
AB - This paper deals with the problem of Blind Source Separation. Contrary to the vast majority of works, we do not assume the statistical independence between the sources and explicitly consider that they are dependent. We introduce three particular models of dependent sources and show that their cumulants have interesting properties. Based on these properties, we investigate the behaviour of classical Blind Source Separation algorithms when applied to these sources: depending on the source vector, the separation may be sucessful or some additionnal indeterminacies can be identified.
UR - https://www.scopus.com/pages/publications/38149036664
U2 - 10.1007/978-3-540-74494-8_2
DO - 10.1007/978-3-540-74494-8_2
M3 - Conference contribution
AN - SCOPUS:38149036664
SN - 9783540744931
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 9
EP - 16
BT - Independent Component Analysis and Signal Separation - 7th International Conference, ICA 2007, Proceedings
PB - Springer Verlag
T2 - 7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007
Y2 - 9 September 2007 through 12 September 2007
ER -