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dc.contributor.authorBayram, S.en_US
dc.contributor.authorGezici, Sinanen_US
dc.date.accessioned2016-02-08T09:47:07Z
dc.date.available2016-02-08T09:47:07Z
dc.date.issued2012-02-20en_US
dc.identifier.issn1051-2004
dc.identifier.urihttp://hdl.handle.net/11693/21491
dc.description.abstractPerformance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing problems. A Neyman-Pearson framework is considered, and the maximization of detection performance under a constraint on the maximum probability of false-alarm is studied. The detection performance is quantified in terms of the sum, the minimum, and the maximum of the detection probabilities corresponding to possible parameter values under the alternative hypothesis. Sufficient conditions under which detection performance can or cannot be improved are derived for each case. Also, statistical characterization of optimal additive noise is provided, and the resulting false-alarm probabilities and bounds on detection performance are investigated. In addition, optimization theoretic approaches to obtaining the probability distribution of optimal additive noise are discussed. Finally, a detection example is presented to investigate the theoretical results.en_US
dc.language.isoEnglishen_US
dc.source.titleDigital Signal Processing: A Review Journalen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.dsp.2012.02.003en_US
dc.subjectBinary hypothesis-testingen_US
dc.subjectComposite hypothesis-testingen_US
dc.subjectLeast-favorable prioren_US
dc.subjectNeyman-Pearsonen_US
dc.subjectStochastic resonance (SR)en_US
dc.subjectBinary compositesen_US
dc.subjectBinary hypothesis-testingen_US
dc.subjectDetection performanceen_US
dc.subjectDetection probabilitiesen_US
dc.subjectIndependent noiseen_US
dc.subjectLeast-favorable prioren_US
dc.subjectMaximum probabilityen_US
dc.subjectNeyman-Pearsonen_US
dc.subjectParameter valuesen_US
dc.subjectStatistical characterizationen_US
dc.subjectStochastic resonancesen_US
dc.subjectSufficient conditionsen_US
dc.subjectTheoretical resulten_US
dc.subjectAdditive noiseen_US
dc.subjectDetectorsen_US
dc.subjectMagnetic resonanceen_US
dc.subjectOptimizationen_US
dc.subjectProbability distributionsen_US
dc.subjectCircuit resonanceen_US
dc.titleStochastic resonance in binary composite hypothesis-testing problems in the Neyman-Pearson frameworken_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage391en_US
dc.citation.epage406en_US
dc.citation.volumeNumber22en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1016/j.dsp.2012.02.003en_US
dc.publisherElsevieren_US
dc.contributor.bilkentauthorGezici, Sinan


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