DocumentCode
1459208
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
Volume
49
Issue
4
fYear
2001
fDate
4/1/2001 12:00:00 AM
Firstpage
694
Lastpage
701
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;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.912913
Filename
912913
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