Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework

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buir.contributor.authorGezici, Sinan
dc.citation.epage3028en_US
dc.citation.spage3025en_US
dc.contributor.authorDülek, Berkanen_US
dc.contributor.authorGezici, Sinanen_US
dc.coverage.spatialKyoto, Japanen_US
dc.date.accessioned2016-02-08T12:12:34Z
dc.date.available2016-02-08T12:12:34Z
dc.date.issued2012-03en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionConference Name: 37th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012
dc.descriptionDate of Conference: 25-30 March 2012
dc.description.abstractPower constrained on-off keying communications systems are investigated in the presence of stochastic signaling and detector randomization. The joint optimal design of decision rules, stochastic signals, and detector randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector randomization can be obtained as the randomization among no more than three Neyman-Pearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented. © 2012 IEEE.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:12:34Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012en
dc.identifier.doi10.1109/ICASSP.2012.6288552en_US
dc.identifier.issn15206149
dc.identifier.urihttp://hdl.handle.net/11693/28154
dc.language.isoEnglishen_US
dc.publisherIEEE
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICASSP.2012.6288552en_US
dc.source.title37th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012en_US
dc.subjectDetectionen_US
dc.subjectDetector randomizationen_US
dc.subjectNeyman-Pearsonen_US
dc.subjectStochastic signalingen_US
dc.subjectCommunications systemsen_US
dc.subjectDecision rulesen_US
dc.subjectDeterministic signalsen_US
dc.subjectGeneric optimizationen_US
dc.subjectNumerical exampleen_US
dc.subjectOptimal designen_US
dc.subjectStochastic signalsen_US
dc.subjectDetectorsen_US
dc.subjectError detectionen_US
dc.subjectOptimizationen_US
dc.subjectSignal processingen_US
dc.subjectStochastic systemsen_US
dc.subjectRandom processesen_US
dc.titleOptimal stochastic signal design and detector randomization in the Neyman-Pearson frameworken_US
dc.typeConference Paperen_US

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