Comparison of approximate maximum likelihood and cumulant based techniques for blind source separation

Author

Yellin, Daniel ; Friedlander, Benjamin

Author_Institution

DSPC, Givat Shmuel, Israel

Volume

1

fYear

1999

Firstpage

591

Abstract

We consider the problem of blind source separation of independent signals which passed through a multi-input multi-output linear time-invariant system. An approximate maximum likelihood estimator and its performance were studied by Yellin and Friedlander (see IEEE Trans. Signal Processing, vol.47, no.5, p.1410-14, 1999, and vol.47, no.6, p.1542-58). The results derived therein are used here to study the performance of source separation techniques based on high order statistics.

Keywords

MIMO systems; approximation theory; higher order statistics; linear systems; maximum likelihood estimation; signal processing; Godard functional; MIMO linear time-invariant system; approximate maximum likelihood estimator; blind source separation; constant modulus functional; cumulant based techniques; high order statistics; independent signals; moments; multi-input multi-output system; performance; Blind source separation; Density functional theory; Gaussian distribution; Maximum likelihood estimation; Performance analysis; Performance gain; Source separation; Statistical analysis; Statistics; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on

ISSN

1058-6393

Print_ISBN

0-7803-5700-0

Type

conf

DOI

10.1109/ACSSC.1999.832398

Filename

832398