Blind source separation using second-order cyclostationary statistics
- Author(s): Abed-Meraim, Karim
- Xiang, Yong
- Manton, Jonathan H
- Hua, Yingbo
- et al.
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.