Blind extraction of cyclostationary signal from convolutional mixtures

Xiang,Y, Ubhayaratne,I, Yang,Z, Rolfe,B and Peng,D 2014, Blind extraction of cyclostationary signal from convolutional mixtures, in ICIEA 2014 : Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications, IEEE, Piscataway, N.J., pp. 857-861, doi: 10.1109/ICIEA.2014.6931282.

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Title Blind extraction of cyclostationary signal from convolutional mixtures
Author(s) Xiang,YORCID iD for Xiang,Y orcid.org/0000-0003-3545-7863
Ubhayaratne,I
Yang,Z
Rolfe,BORCID iD for Rolfe,B orcid.org/0000-0001-8516-6170
Peng,D
Conference name Industrial Electronics and Applications. Conference (9th: 2014: Hangzhou, China)
Conference location Hangzhou, China
Conference dates 9-11 Jun. 2014
Title of proceedings ICIEA 2014 : Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications
Editor(s) [Unknown]
Publication date 2014
Conference series Industrial Electronics and Applications Conference
Start page 857
End page 861
Total pages 5
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Blind extraction
Cyclostationary signal
Summary Extracting a signal of interest from available measurements is a challenging problem. One property which can be utilized to extract the signal is cyclostationarity, which exists in many signals. Various blind source separation methods based on cyclostationarity have been reported in the literature but they assume that the mixing system is instantaneous. In this paper, we propose a method for blind extraction of cyclostationary signal from convolutional mixtures. Given that the signal of interest has a unique cyclostationary frequency and the sensors are placed close to the concerned signal, we show that the signal of interest can be estimated from the measured data. Simulations results show the effectiveness of our method.
ISBN 9781479943166
Language eng
DOI 10.1109/ICIEA.2014.6931282
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
Socio Economic Objective 861799 Communication Equipment not elsewhere classified
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Grant ID DP110102076
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30068210

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