TY - JOUR
T1 - A new joint diagonalization algorithm with application in blind source separation
AU - Wang, Fuxiang
AU - Liu, Zhongkan
AU - Zhang, Jun
PY - 2006/1
Y1 - 2006/1
N2 - In this letter, we present a new nonorthogonal algorithm for joint diagonalization of a set of symmetric matrices. The algorithm alternates between updates of individual demixing matrix rows, and the update of each row is transferred to solving the eigenvector problem. By using some blind source separation simulations, we show that the algorithm obviously obtains an improved performance when the signal-to-noise ratio of the observed signals is relatively low.
AB - In this letter, we present a new nonorthogonal algorithm for joint diagonalization of a set of symmetric matrices. The algorithm alternates between updates of individual demixing matrix rows, and the update of each row is transferred to solving the eigenvector problem. By using some blind source separation simulations, we show that the algorithm obviously obtains an improved performance when the signal-to-noise ratio of the observed signals is relatively low.
KW - Blind source separation (BSS)
KW - Eigenvalue and eigenvector
KW - Interference-to-signal ratio (ISR)
KW - Joint diagonalization
UR - https://www.scopus.com/pages/publications/30444446914
U2 - 10.1109/LSP.2005.860542
DO - 10.1109/LSP.2005.860542
M3 - 文章
AN - SCOPUS:30444446914
SN - 1070-9908
VL - 13
SP - 41
EP - 44
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
IS - 1
ER -