Online modulation recognition of analog communication signals using neural network

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dc.contributor.authorGuldemir, H.
dc.contributor.authorSengur, A.
dc.date.accessioned2026-08-12T17:44:45Z
dc.date.issued2007
dc.departmentFırat Üniversitesi
dc.description.abstractIn this paper, a neural network based online analog modulation recognition of communication signals is presented. The proposed system can discriminate between amplitude modulation (AM), frequency modulation (FM), double sideband (DSB), upper sideband (USB), lower sideband (LSB) and continuous wave (CW) modulations. A matlab graphical user interface (GUI) is designed to see the intercepted signal, its power spectral density, frequency and modulation type on the screen of the personnel computer. To achieve correct classification, extensive simulations have been done for training the neural network. Theoretical simulations and experimental results indicate good performance even at signal-to-noise ratios as low as 5 dB. (c) 2006 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.eswa.2006.04.015
dc.identifier.endpage214
dc.identifier.issn0957-4174
dc.identifier.issue1
dc.identifier.orcid0000-0003-0491-8348
dc.identifier.orcid0000-0003-1614-2639
dc.identifier.scopus2-s2.0-33845648833
dc.identifier.scopusqualityQ1
dc.identifier.startpage206
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2006.04.015
dc.identifier.urihttps://hdl.handle.net/11508/60401
dc.identifier.volume33
dc.identifier.wosWOS:000244110600020
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofExpert Systems with Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectmodulation
dc.subjectrecognition
dc.subjectneural network
dc.subjectclassification
dc.subjectkey features
dc.titleOnline modulation recognition of analog communication signals using neural network
dc.typeArticle

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