DocumentCode :
935692
Title :
Nonorthogonal Joint Diagonalization Algorithm Based on Trigonometric Parameterization
Author :
Wang, Fuxiang ; Liu, Zhongkan ; Zhang, Jun
Author_Institution :
Beihang Univ., Beijing
Volume :
55
Issue :
11
fYear :
2007
Firstpage :
5299
Lastpage :
5308
Abstract :
The joint diagonalization technique is an important type of method for blind source separation. In this paper, a new approach is presented to joint diagonalization for a set of symmetric matrices with a general (and not necessarily orthogonal) matrix. The approach performs joint diagonalization via a series of symmetric eigen decompositions, including merits of simplicity, effectiveness, and computational efficiency. Simulation results demonstrate the potential improvement of the performance in the context of blind source separation.
Keywords :
blind source separation; eigenvalues and eigenfunctions; blind source separation; eigen decompositions; nonorthogonal joint diagonalization algorithm; trigonometric parameterization; Blind source separation; Computational efficiency; Computational modeling; Context modeling; Cost function; Jacobian matrices; Matrix decomposition; Signal processing algorithms; Source separation; Symmetric matrices; Blind source separation; independent component analysis; joint diagonalization;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2007.899378
Filename :
4355278
Link To Document :
بازگشت