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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 Peng
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.

History

Event

Industrial Electronics and Applications. Conference (9th: 2014: Hangzhou, China)

Pagination

857 - 861

Publisher

IEEE

Location

Hangzhou, China

Place of publication

Piscataway, N.J.

Start date

2014-06-09

End date

2014-06-11

ISBN-13

9781479943166

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2014, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICIEA 2014 : Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications