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dc.contributor.authorRamírez García, David
dc.contributor.authorScharf, Louis L. 
dc.contributor.authorVía Rodríguez, Javier 
dc.contributor.authorSantamaría Caballero, Luis Ignacio 
dc.contributor.authorSchreier, Peter J.
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2016-11-02T14:32:53Z
dc.date.available2016-11-02T14:32:53Z
dc.date.issued2014
dc.identifier.isbn978-1-4799-2894-1
dc.identifier.isbn978-1-4799-2893-4
dc.identifier.isbn978-1-4799-2892-7
dc.identifier.otherTEC2010-19545-C04-03es_ES
dc.identifier.otherCSD2008-00010es_ES
dc.identifier.urihttp://hdl.handle.net/10902/9441
dc.description.abstractWe derive the generalized likelihood ratio test (GLRT) for detecting cyclostationarity in scalar- valued time series. The main idea behind our approach is Gladyshev’s relationship, which states that when the scalar-valued cyclostationary signal is blocked at the known cycle period it produces a vectorvalued wide-sense stationary (WSS) process. This result amounts to saying that the covariance matrix of the vector obtained by stacking all observations of the time series is block-Toeplitz if the signal is cyclostationary, and Toeplitz if the signal is wide-sense stationary. The derivation of the GLRT requires the maximum likelihood estimates of Toeplitz and block-Toeplitz matrices. This can be managed asymptotically (for large number of samples) exploiting Szegö’s theorem and its generalization for vector-valued processes. Simulation results show the good performance of the proposed GLRT.es_ES
dc.description.sponsorshipThe work of L. Scharf was supported by the Airforce Office of Scientific Research under contract FA9550-10-1-0241. The work of I. Santamaría and J. Vía was supported by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under project COSIMA (TEC2010-19545-C04-03) and project COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 Program). The work of P. Schreier was supported by the Alfried Krupp von Bohlen und Halbach Foundation, under its program “Return of German scientists from abroad.es_ES
dc.format.extent5 p.es_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rights© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.es_ES
dc.sourceIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Florence, Italy, 2014, 3415-3419es_ES
dc.subject.otherCyclostationarityes_ES
dc.subject.otherGeneralized likelihood ratio test (GLRT)es_ES
dc.subject.otherHypothesis testes_ES
dc.subject.otherMaximum likelihood (ML) estimationes_ES
dc.subject.otherToeplitz matriceses_ES
dc.titleAn asymptotic GLRT for the detection of cyclostationary signalses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1109/ICASSP.2014.6854234es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1109/ICASSP.2014.6854234
dc.type.versionacceptedVersiones_ES


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