Average fisher information optimization for quantized measurements using additive independent noise

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buir.contributor.authorGezici, Sinan
dc.citation.epage180en_US
dc.citation.spage177en_US
dc.contributor.authorBalkan, Gokce Osmanen_US
dc.contributor.authorGezici, Sinanen_US
dc.coverage.spatialDıyarbakır, Turkeyen_US
dc.date.accessioned2016-02-08T12:21:30Z
dc.date.available2016-02-08T12:21:30Z
dc.date.issued2010en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 22-24 April 2010en_US
dc.description.abstractAdding noise to nonlinear systems can enhance their performance. Additive noise benefits are observed also in parameter estimation problems based on quantized observations. In this study, the purpose is to find the optimal probability density function of additive noise, which is applied to observations before quantization, in those problems. First, optimal probability density function of noise is formulated in terms of an average Fisher information maximization problem. Then, it is proven that optimal additive "noise" can be represented by a constant signal level. This result, which means that randomization of additive signal levels is not needed for average Fisher information maximization, is supported with two numerical examples. ©2010 IEEE.en_US
dc.identifier.doi10.1109/SIU.2010.5653626en_US
dc.identifier.urihttp://hdl.handle.net/11693/28469
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2010.5653626en_US
dc.source.title2010 IEEE 18th Signal Processing and Communications Applications Conferenceen_US
dc.subjectFisher informationen_US
dc.subjectIndependent noiseen_US
dc.subjectNumerical exampleen_US
dc.subjectQuantized measurementsen_US
dc.subjectQuantized observationsen_US
dc.subjectSignal levelen_US
dc.subjectAdditive noiseen_US
dc.subjectFisher information matrixen_US
dc.subjectOptimizationen_US
dc.subjectParameter estimationen_US
dc.subjectSignal processingen_US
dc.subjectProbability density functionen_US
dc.titleAverage fisher information optimization for quantized measurements using additive independent noiseen_US
dc.title.alternativeNicemlenmiş ölçümlere bağimsiz gürültü eklenerek ortalama fisher bilgisi optimizasyonuen_US
dc.typeConference Paperen_US
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Average fisher information optimization for quantized measurements using additive independent noise [Nicemlenmiş ölçümlere baǧimsiz gürültü eklenerek ortalama fisher bilgisi optimizasyonu].pdf
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