Saddlepoint Approximation of the Error Probability of Binary Hypothesis Testing

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dc.contributor.author Vázquez Vilar, Gonzalo
dc.contributor.author Guillén i Fàbregas, Albert
dc.contributor.author Koch, Tobias Mirco
dc.contributor.author Lancho Serrano, Alejandro
dc.date.accessioned 2018-10-03T12:42:22Z
dc.date.available 2018-10-03T12:42:22Z
dc.date.issued 2018-08-16
dc.identifier.bibliographicCitation IEEE International Symposium on Information Theory (ISIT 2018), 17-22 June 2018, Vail, Colorado, USA. [Proceedings], 5 p.
dc.identifier.isbn 978-1-5386-4780-6
dc.identifier.issn 2157-8117
dc.identifier.uri http://hdl.handle.net/10016/27525
dc.description.abstract We propose a saddlepoint approximation of the error probability of a binary hypothesis test between two i.i.d. distributions. The approximation is accurate, simple to compute, and yields a unified analysis in different asymptotic regimes. The proposed formulation is used to efficiently compute the meta-converse lower bound for moderate block-lengths in several cases of interest.
dc.description.sponsorship This work has been funded in part by the European Research Council (ERC) under grants 714161 and 725411, by the Spanish Ministry of Economy and Competitiveness under grants TEC2013-41718-R, RYC-201416332, IJCI-2015-27020 and TEC2016-78434-C3 (AEI/FEDER, EU), by the Madrid Autonomous Community under grant S2103/ICE-2845 and by the Spanish Ministry of Education, Culture and Sport under grant FPU14/01274.
dc.format.extent 5
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2018 IEEE.
dc.subject.other Error probability
dc.subject.other Testing
dc.subject.other Random variables
dc.subject.other AWGN channels
dc.subject.other Laplace equations
dc.subject.other Gaussian distribution
dc.title Saddlepoint Approximation of the Error Probability of Binary Hypothesis Testing
dc.type bookPart
dc.type conferenceObject
dc.subject.eciencia Electrónica
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/714161
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/725411
dc.relation.projectID Gobierno de España. TEC2013-41718-R
dc.relation.projectID Gobierno de España. RYC-2014-16332
dc.relation.projectID Gobierno de España. IJCI-2015-27020
dc.relation.projectID Gobierno de España. TEC2016-78434-C3 (AEI/FEDER, EU)
dc.relation.projectID Gobierno de España. FPU14/01274
dc.relation.projectID Comunidad de Madrid. S2103/ICE-2845
dc.type.version acceptedVersion
dc.relation.eventdate 2018-06-17
dc.relation.eventplace Vail., Colorado, USA
dc.relation.eventtitle IEEE International Symposium on Information Theory (ISIT 2018)
dc.identifier.publicationfirstpage 1
dc.identifier.publicationlastpage 5
dc.identifier.publicationtitle IEEE International Symposium on Information Theory (ISIT 2018) [Proceedings]
dc.identifier.uxxi CC/0000027956
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