Ionogram scaling using Hidden Markov Models

buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.contributor.authorGök, Gökhanen_US
dc.contributor.authorAlp, Y. K.en_US
dc.contributor.authorArıkan, Orhanen_US
dc.contributor.authorArikan, F.en_US
dc.coverage.spatialIzmir, Turkeyen_US
dc.date.accessioned2019-02-21T16:05:06Zen_US
dc.date.available2019-02-21T16:05:06Zen_US
dc.date.issued2018en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 2-5 May 2018en_US
dc.description.abstractIn this paper, a novel method for electron density reconstruction using ionosonde data is proposed. Proposed technique uses Hidden Markov Models for extracting echoes that provides valuable information about electron density distribution in order to provide input to a model based optimization technique that reconstructs the electron density distribution by solving model parameters. Analysis on real ionosonde data shows that proposed technique outperforms standard techniques in the literature.en_US
dc.description.provenanceMade available in DSpace on 2019-02-21T16:05:06Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.identifier.doi10.1109/SIU.2018.8404620en_US
dc.identifier.isbn9781538615010en_US
dc.identifier.urihttp://hdl.handle.net/11693/50231en_US
dc.language.isoTurkishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttps://doi.org/10.1109/SIU.2018.8404620en_US
dc.source.title2018 26th Signal Processing and Communications Applications Conference (SIU)en_US
dc.subjectElectron density re-consturctionen_US
dc.subjectHidden Markov Modelsen_US
dc.subjectIonogram scalingen_US
dc.subjectIonosondeen_US
dc.subjectModel based optimizationen_US
dc.subjectRemote sensingen_US
dc.titleIonogram scaling using Hidden Markov Modelsen_US
dc.title.alternativeSaklı markov modelleri ile iyonogram ölçeklendirmesien_US
dc.typeConference Paperen_US

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