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dc.contributor.authorBiskin, Osman Tayfun
dc.contributor.authorAkay, Olcay
dc.date.accessioned2021-02-12T18:47:47Z
dc.date.available2021-02-12T18:47:47Z
dc.date.issued2015
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11147/10314
dc.description23nd Signal Processing and Communications Applications Conference (SIU)en_US
dc.description.abstractIn this study, robust nonparametric spectral estimation methods for non-Gaussian environments are proposed. For this aim, the autocorrelation function estimator obtained from sample spatial sign covariance matrix is used together with classical nonparametric spectral estimation methods such as periodogram and Blackman-Tukey. Performances of classical spectral estimation methods and robust methods suggested in this study are compared by applying them to one Gaussian process and one non-Gaussian heavy-tailed stochastic process. The results obtained show that, for non-Gaussian environments, the proposed robust nonparametric spectral estimation methods could perform better compared to the classical methods.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Univen_US
dc.language.isoturen_US
dc.publisherIEEEen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRobust estimationen_US
dc.subjectnonparametric spectral estimatiomen_US
dc.subjectsample spatial sign covariance matrixen_US
dc.subjectheavy-tailed distributionsen_US
dc.titleA Method for Robustifying Classical Nonparametric Spectral Estimation Techniquesen_US
dc.typeconferenceObjecten_US
dc.typeconferenceObjecten_US
dc.relation.journal2015 23Rd Signal Processing And Communications Applications Conference (Siu)en_US
dc.contributor.departmentIzmir Isntitute of Technologyen_US
dc.identifier.startpage2274en_US
dc.identifier.endpage2277en_US
dc.identifier.wosWOS:000380500900550
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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