Estimation of the Nonlinearity Degree for Polynomial Autoregressive Processes With Rjmcmc

dc.contributor.author Karakuş, Oktay
dc.contributor.author Kuruoğlu, Ercan E.
dc.contributor.author Altınkaya, Mustafa Aziz
dc.contributor.other 03.05. Department of Electrical and Electronics Engineering
dc.contributor.other 03. Faculty of Engineering
dc.contributor.other 01. Izmir Institute of Technology
dc.date.accessioned 2021-01-24T18:31:44Z
dc.date.available 2021-01-24T18:31:44Z
dc.date.issued 2015
dc.description 23rd European Signal Processing Conference (EUSIPCO) en_US
dc.description.abstract Despite the popularity of linear process models in signal and image processing, various real life phenomena exhibit nonlinear characteristics. Compromising between the realistic and computationally heavy nonlinear models and the simplicity of linear estimation methods, linear in the parameters nonlinear models such as polynomial autoregressive (PAR) models have been accessible analytical tools for modelling such phenomena. In this work, we aim to demonstrate the potentials of Reversible Jump Markov Chain Monte Carlo (RSMCMC) which is a successful statistical tool in model dimension estimation in nonlinear process identification. We explore the capability of RJMCMC in jumping not only between spaces with different dimensions, but also between different classes of models. In particular, we demonstrate the success of RJMCMC in sampling in linear and nonlinear spaces of varying dimensions for the estimation of PAR processes. en_US
dc.description.sponsorship EURECOM en_US
dc.identifier.isbn 978-0-9928-6263-3
dc.identifier.issn 2076-1465
dc.identifier.uri https://hdl.handle.net/11147/9942
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof 2015 23rd European Signal Processing Conference, EUSIPCO 2015 en_US
dc.relation.ispartofseries European Signal Processing Conference
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Polynomial AR en_US
dc.subject Reversible Jump MCMC en_US
dc.subject Nonlinearity degree estimation en_US
dc.title Estimation of the Nonlinearity Degree for Polynomial Autoregressive Processes With Rjmcmc en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Karakuş, Oktay
gdc.author.institutional Altınkaya, Mustafa Aziz
gdc.coar.access metadata only access
gdc.coar.type text::conference output
gdc.description.department İzmir Institute of Technology. Electrical and Electronics Engineering en_US
gdc.description.departmenttemp [Karakus, Oktay; Altinkaya, Mustafa A.] Izmir Inst Technol, Elect Elect Engn, Izmir, Turkey; [Kuruoglu, Ercan E.] ISTI CNR, I-56124 Pisa, Italy en_US
gdc.description.endpage 957 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 953 en_US
gdc.description.wosquality N/A
gdc.identifier.wos WOS:000377943800192
gdc.wos.citedcount 5
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