Title :
Joint-diagonalization of cumulant tensors and source separation
Author_Institution :
MS-GESSY, ISITV, La Valette du Var, France
Abstract :
We extend the results leading the popular JADE and STOTD algorithms to cumulants of any order greater than or equal to three. We first exhibit a new contrast function which constitutes an unified framework for the underlying contrasts of JADE and STOTD which thus appear as particular cases. Then we generalize the link between these new contrasts and a joint-diagonalization criterion. Moreover for the generalized JADE´s contrast, the analytical optimal solution in the case of two sources is derived and shown to keep the same simple expression whatever the cumulant order. Finally, some computer simulations illustrate the potential advantage one can take considering statistics of different orders for the joint-diagonalization of cumulant matrices
Keywords :
higher order statistics; matrix algebra; signal processing; tensors; JADE algorithm; STOTD algorithm; computer simulations; contrast function; cumulant matrices; cumulant tensors; joint-diagonalization criterion; optimal solution; source separation; Algorithm design and analysis; Artificial intelligence; Covariance matrix; Independent component analysis; Reactive power; Source separation; Statistics; Tensile stress;
Conference_Titel :
Statistical Signal and Array Processing, 2000. Proceedings of the Tenth IEEE Workshop on
Conference_Location :
Pocono Manor, PA
Print_ISBN :
0-7803-5988-7
DOI :
10.1109/SSAP.2000.870140