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Sphericity minimum description length: asymptotic performance under unknown noise variance

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dc.contributor.author Font-Segura, Josep
dc.contributor.author Riba, Jaume
dc.contributor.author Vázquez, Gregori
dc.date.accessioned 2024-01-30T07:24:36Z
dc.date.available 2024-01-30T07:24:36Z
dc.date.issued 2015
dc.identifier.citation Font-Segura J, Riba J, Vazquez G. Sphericity minimum description length: asymptotic performance under unknown noise variance. In: 2015 IEEE International Symposium on Information Theory (ISIT); 2015 Jun 14-19; Hong Kong. [Piscataway]: IEEE; 2015. p. 1615–19. DOI: 10.1109/ISIT.2015.7282729
dc.identifier.isbn 9781467377058
dc.identifier.issn 2157-8095
dc.identifier.uri http://hdl.handle.net/10230/58875
dc.description Comunicació presentada a 2015 IEEE International Symposium on Information Theory (ISIT), celebrada del 14 al 19 de juny de 2015 a Hong Kong
dc.description.abstract This paper revisits the model order selection problem in the context of second-order spectrum sensing in cognitive radio. Taking advantage of the recent interest on the generalized likelihood ratio (GLR), the asymptotic performance of the minimum description length (MDL) rule under unknown noise variance is addressed. In particular, by exploiting the asymptotically Chi-squared distribution of the GLR, a complete characterization of the error probability is reported, instead of approximating only the missed-detection probability as done in the literature
dc.description.sponsorship This work has been partially funded by the the Spanish Government (Ministerio de Econom´ıa y Competitividad) under TEC2010-21245-C02- 01 (DYNACS), TEC2013-47020C2-2-R COMPASS (COMPASS), CONSOLIDER INGENIO CSD2008-00010 (COMONSENS), CENIT CEN20101019 (THOFU), and the Catalan Government (AGAUR) under Grant 2014 SGR 60 and Fellowship FI-2010.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof 2015 IEEE International Symposium on Information Theory (ISIT); 2015 Jun 14-19; Hong Kong. [Piscataway]: IEEE; 2015. p. 1615–19.
dc.rights © 2015 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. http://dx.doi.org/10.1109/ISIT.2015.7282729
dc.title Sphericity minimum description length: asymptotic performance under unknown noise variance
dc.type info:eu-repo/semantics/conferenceObject
dc.identifier.doi http://dx.doi.org/10.1109/ISIT.2015.7282729
dc.subject.keyword Model order selection
dc.subject.keyword Minimum description length
dc.subject.keyword Generalized likelihood ratio
dc.subject.keyword Noise uncertainty
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/CSD2008-00010
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/TEC2010-21245-C02-01
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/ TEC2013-47020C2-2-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion

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