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

Volume

13

Issue

1

fYear

2006

Firstpage

41

Lastpage

44

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;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2005.860542

Filename

1561207