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Online adaptive blind deconvolution based on third-order moments
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2005 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 12, 863-866 p.Article in journal (Refereed) Published
Abstract [en]

Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel.

Place, publisher, year, edition, pages
2005. Vol. 12, no 12, 863-866 p.
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-10529DOI: 10.1109/LSP.2005.859496Local ID: 9588b2d0-7f1b-11db-8824-000ea68e967bOAI: oai:DiVA.org:ltu-10529DiVA: diva2:983474
Note
Validerad; 2005; 20061128 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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CiteExportLink to record
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  • apa
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