Title :
A new joint diagonalization algorithm with application in blind source separation
Author :
Fuxiang, Wang ; Zhongkan, Liu ; Jun, Zhang
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
Abstract :
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.
Keywords :
blind source separation; eigenvalues and eigenfunctions; interference (signal); BSS; blind source separation simulation; eigenvalue-eigenvector problem; joint diagonalization; nonorthogonal algorithm; signal interference; symmetric matrix; Additive noise; Blind source separation; Character generation; Cost function; Iterative algorithms; Noise level; Signal processing; Signal processing algorithms; Source separation; Symmetric matrices; Blind source separation (BSS); eigenvalue and eigenvector; interference-to-signal ratio (ISR); joint diagonalization;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2005.860542
