Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/7655
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dc.contributor.authorKarakuş, Oktay-
dc.contributor.authorKuruoğlu, Ercan Engin-
dc.contributor.authorAltınkaya, Mustafa Aziz-
dc.date.accessioned2020-02-04T11:22:05Z
dc.date.available2020-02-04T11:22:05Z
dc.date.issued2018-12en_US
dc.identifier.citationKarakuş, O., Kuruoğlu, E. E., and Altınkaya, M. A. (2018). Beyond trans-dimensional RJMCMC with a case study in impulsive data modeling. Signal Processing, 153, 396-410. doi:10.1016/j.sigpro.2018.07.028en_US
dc.identifier.issn0165-1684
dc.identifier.issn0165-1684-
dc.identifier.urihttps://doi.org/10.1016/j.sigpro.2018.07.028
dc.identifier.urihttps://hdl.handle.net/11147/7655
dc.description.abstractReversible jump Markov chain Monte Carlo (RJMCMC) is a Bayesian model estimation method, which has been generally used for trans-dimensional sampling and model order selection studies in the literature. In this study, we draw attention to unexplored potentials of RJMCMC beyond trans-dimensional sampling. the proposed usage, which we call trans-space RJMCMC exploits the original formulation to explore spaces of different classes or structures. This provides flexibility in using different types of candidate classes in the combined model space such as spaces of linear and nonlinear models or of various distribution families. As an application, we looked into a special case of trans-space sampling, namely trans-distributional RJMCMC in impulsive data modeling. In many areas such as seismology, radar, image, using Gaussian models is a common practice due to analytical ease. However, many noise processes do not follow a Gaussian character and generally exhibit events too impulsive to be successfully described by the Gaussian model. We test the proposed usage of RJMCMC to choose between various impulsive distribution families to model both synthetically generated noise processes and real-life measurements on power line communications impulsive noises and 2-D discrete wavelet transform coefficients.en_US
dc.description.sponsorshipTUBITAK; College of Natural Resources, University of California Berkeleyen_US
dc.language.isoenen_US
dc.publisherElsevier Ltd.en_US
dc.relation.ispartofSignal Processingen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGeneralized Gaussian distributionen_US
dc.subjectImpulsive data modelingen_US
dc.subjectPLC impulsive noise modelingen_US
dc.subjectReversible jump MCMCen_US
dc.subjectWavelet coefficients modelingen_US
dc.titleBeyond trans-dimensional RJMCMC with a case study in impulsive data modelingen_US
dc.typeArticleen_US
dc.authorid0000-0001-8048-5850en_US
dc.institutionauthorKarakuş, Oktay-
dc.institutionauthorAltınkaya, Mustafa Aziz-
dc.departmentİzmir Institute of Technology. Electrical and Electronics Engineeringen_US
dc.identifier.volume153en_US
dc.identifier.startpage396en_US
dc.identifier.endpage410en_US
dc.identifier.wosWOS:000445989100035en_US
dc.identifier.scopus2-s2.0-85051832245en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.sigpro.2018.07.028-
dc.relation.doi10.1016/j.sigpro.2018.07.028en_US
dc.coverage.doi10.1016/j.sigpro.2018.07.028en_US
dc.identifier.wosqualityQ1-
dc.identifier.scopusqualityQ1-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.languageiso639-1en-
crisitem.author.dept03.05. Department of Electrical and Electronics Engineering-
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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