Title :
Blind source-separation using second-order cyclostationary statistics
Author :
Abed-Meraim, Karim ; Xiang, Yong ; Manton, Jonathan H. ; Hua, Yingbo
Author_Institution :
Dept. of Signal Processing, Ecole Nat. Superieure des Telecommun., Paris, France
fDate :
4/1/2001 12:00:00 AM
Abstract :
This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast function. This algorithm separates the sources even when they do not have distinct cycle frequencies
Keywords :
identification; iterative methods; signal processing; statistical analysis; blind source-separation; contrast function minimisation; cyclostationary source signals; identifiability criteria; iterative algorithm; second-order cyclostationary statistics; separability criteria; Blind source separation; Frequency; Iterative algorithms; Remote sensing; Sensor arrays; Signal processing; Source separation; Speech processing; Statistics; Sufficient conditions;
Journal_Title :
Signal Processing, IEEE Transactions on
