New Negentropy Optimization Schemes for Blind Signal Extraction of Complex Valued Sources
Loading...
Date
2015-04
Authors
Xu, Peng-cheng
Shen, Yue-hong
Li, Hui
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Altmetrics
Abstract
Blind signal extraction, a hot issue in the field of communication signal processing, aims to retrieve the sources through the optimization of contrast functions. Many contrasts based on higher-order statistics such as kurtosis, usually behave sensitive to outliers. Thus, to achieve robust results, nonlinear functions are utilized as contrasts to approximate the negentropy criterion, which is also a classical metric for non-Gaussianity. However, existing methods generally have a high computational cost, hence leading us to address the problem of efficient optimization of contrast function. More precisely, we design a novel “reference-based” contrast function based on negentropy approximations, and then propose a new family of algorithms (Alg.1 and Alg.2) to maximize it. Simulations confirm the convergence of our method to a separating solution, which is also analyzed in theory. We also validate the theoretic complexity analysis that Alg.2 has a much lower computational cost than Alg.1 and existing optimization methods based on negentropy criterion. Finally, experiments for the separation of single sideband signals illustrate that our method has good prospects in real-world applications.
Description
Citation
Radioengineering. 2015 vol. 24, č. 1, s. 262-271. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2015/15_01_0262_0271.pdf
http://www.radioeng.cz/fulltexts/2015/15_01_0262_0271.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en