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2017 | OriginalPaper | Chapter

Blind Separation of Cyclostationary Sources with Common Cyclic Frequencies

Authors : Amine Brahmi, Hicham Ghennioui, Christophe Corbier, M’hammed Lahbabi, François Guillet

Published in: Latent Variable Analysis and Signal Separation

Publisher: Springer International Publishing

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Abstract

We propose a new method for blind source separation of cyclostationary sources, whose cyclic frequencies are unknown and may share one or more common cyclic frequencies. The suggested method exploits the second-order cyclostationarity statistics of observation signals to build a set of matrices which has a particular algebraic structure. We also introduce an automatic point selection procedure for the determination of these matrices to be joint diagonalized in order to identify the mixing matrix and recover the source signals as a result. The non-unitary joint diagonalization is ensured by Broyden-Fletcher-Goldfarb-Shanno (BFGS) method which is the most commonly used update strategy for implementing a quasi-newton technique. Numerical simulations are provided to demonstrate the usefulness of the proposed method in the context of digital communications and to compare it with another method based upon an unitary joint diagonalization algorithm.

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previous chapter Fast Disentanglement-Based Blind Quantum Source Separation and Process Tomography: A Closed-Form Solution Using a Feedback Classical Adapting Structure
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Metadata
Title
Blind Separation of Cyclostationary Sources with Common Cyclic Frequencies
Authors
Amine Brahmi
Hicham Ghennioui
Christophe Corbier
M’hammed Lahbabi
François Guillet
Copyright Year
2017
Book
Latent Variable Analysis and Signal Separation

Print ISBN: 978-3-319-53546-3

Electronic ISBN: 978-3-319-53547-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-53547-0_42

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