Blind source-separation using second-order cyclostationary statistics
Karim Abed‐Meraim, Yong Xiang, Jonathan H. Manton, Yingbo Hua · IEEE Transactions on Signal Processing · 2001
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.