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Blind extraction of cyclostationary signal from convolutional mixtures
conference contribution
posted on 2014-10-20, 00:00 authored by Yong XiangYong Xiang, Kongalage Nishchitha Indivarie Ubhayaratne, Zuyuan Yang, Bernard RolfeBernard Rolfe, D PengExtracting 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.
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Event
Industrial Electronics and Applications. Conference (9th: 2014: Hangzhou, China)Pagination
857 - 861Publisher
IEEELocation
Hangzhou, ChinaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2014-06-09End date
2014-06-11ISBN-13
9781479943166Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2014, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
ICIEA 2014 : Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and ApplicationsUsage metrics
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