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dc.contributor.authorErdem, Tanju
dc.contributor.authorErcan, Ali Özer
dc.date.accessioned2016-06-29T13:04:29Z
dc.date.available2016-06-29T13:04:29Z
dc.date.issued2016
dc.identifier.issn1863-1711
dc.identifier.urihttp://hdl.handle.net/10679/4091
dc.identifier.urihttp://link.springer.com/article/10.1007%2Fs11760-016-0888-3
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractBispectra are third-order statistics that have been used extensively in analyzing nonlinear and non-Gaussian data. Bispectrum of a process can be computed as the Fourier transform of its bicumulant sequence. It is in general hard to obtain reliable bicumulant samples at high lags since they suffer from large estimation variance. This paper proposes a novel approach for estimating bispectrum from a small set of given low lag bicumulant samples. The proposed approach employs an underlying MISO system composed of stable and causal autoregressive components. We provide an algorithm to compute the parameters of such a system from the given bicumulant samples. Experimental results show that our approach is capable of representing non-polynomial spectra with a stable underlying system model, which results in better bispectrum estimation than the leading algorithm in the literature.
dc.language.isoengen_US
dc.publisherSpringer International Publishing
dc.relation.ispartofSignal, Image and Video Processing
dc.rightsrestrictedAccess
dc.titleBispectrum estimation using a MISO autoregressive modelen_US
dc.typeArticleen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-8841-1642 & YÖK ID 45777) Erdem, Tanju
dc.contributor.authorID(ORCID 0000-0003-1126-8259 & YÖK ID 35788) Ercan, Ali
dc.contributor.ozuauthorErdem, Tanju
dc.contributor.ozuauthorErcan, Ali Özer
dc.identifier.wosWOS:000382363300009
dc.identifier.doi10.1007/s11760-016-0888-3
dc.subject.keywordsBispectrum estimation
dc.subject.keywordsBicumulant sequence
dc.subject.keywordsMISO autoregressive system
dc.subject.keywordsSystem identification
dc.identifier.scopusSCOPUS:2-s2.0-84961661651
dc.contributor.authorMale2
dc.relation.publicationcategoryArticle - International Refereed Journal - Institutional Academic Staff


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