Noise enhanced hypothesis-testing according to restricted Neyman-Pearson criterion

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buir.contributor.authorGezici, Sinan
dc.citation.epage27en_US
dc.citation.spage17en_US
dc.citation.volumeNumber25en_US
dc.contributor.authorBayram, S.en_US
dc.contributor.authorGultekin, S.en_US
dc.contributor.authorGezici, Sinanen_US
dc.date.accessioned2016-02-08T10:58:28Z
dc.date.available2016-02-08T10:58:28Z
dc.date.issued2014en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractNoise enhanced hypothesis-testing is studied according to the restricted Neyman-Pearson (NP) criterion. First, a problem formulation is presented for obtaining the optimal probability distribution of additive noise in the restricted NP framework. Then, sufficient conditions for improvability and nonimprovability are derived in order to specify if additive noise can or cannot improve detection performance over scenarios in which no additive noise is employed. Also, for the special case of a finite number of possible parameter values under each hypothesis, it is shown that the optimal additive noise can be represented by a discrete random variable with a certain number of point masses. In addition, particular improvability conditions are derived for that special case. Finally, theoretical results are provided for a numerical example and improvements via additive noise are illustrated. © 2013 Elsevier Inc.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:58:28Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2014en
dc.identifier.doi10.1016/j.dsp.2013.10.014en_US
dc.identifier.issn1051-2004
dc.identifier.urihttp://hdl.handle.net/11693/26337
dc.language.isoEnglishen_US
dc.publisherAcademic Pressen_US
dc.publisher
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.dsp.2013.10.014en_US
dc.source.titleDigital Signal Processingen_US
dc.subjectDetectionen_US
dc.subjectComposite hypothesisen_US
dc.subjectNoise benefitsen_US
dc.subjectStochastic resonanceen_US
dc.subjectRestricted Neyman–Pearsonen_US
dc.titleNoise enhanced hypothesis-testing according to restricted Neyman-Pearson criterionen_US
dc.typeArticleen_US

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