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dc.contributor.authorÖzfidan, Özgüren_US
dc.contributor.authorBayazıt, Uluğen_US
dc.contributor.authorÇırpan, Hakan Alien_US
dc.date.accessioned2019-08-31T12:10:23Z
dc.date.accessioned2019-08-05T16:03:06Z
dc.date.available2019-08-31T12:10:23Z
dc.date.available2019-08-05T16:03:06Z
dc.date.issued2007
dc.identifier.citationÖzfidan, O., Bayazıt, U., & Çırpan, H. A. (2007). Cluster based sensor scheduling in a target tracking application with particle filtering. Paper presented at the 1741-1746. doi:10.1109/ISIE.2007.4374868en_US
dc.identifier.isbn9781424407545
dc.identifier.isbn9781424407552
dc.identifier.isbn1424407559
dc.identifier.issn2163-5137
dc.identifier.issn2163-5145
dc.identifier.otherWOS:000252265104001
dc.identifier.urihttps://hdl.handle.net/11729/1808
dc.identifier.urihttps://dx.doi.org/10.1109/ISIE.2007.4374868
dc.description.abstractIn multi-sensor applications management of sensors is necessary for the classification of data they produce and for the efficient use of sensors as well. One of the important aspects in sensor management is the sensor scheduling. By scheduling the sensors, serious reductions can be achieved in the cost of bandwidth, power, and computation. In this work a simple solution for the problem of sensor scheduling in a multi-sensor target tracking application is presented. Due to non-linearity of the problem itself, proposed solution is presented in the framework of non-linear Bayesian estimation.en_US
dc.description.sponsorshipThis research has been funded by the The Scientific & Technological Research Council of Turkey (TUB ITAK), Project No: 104E130 and also supported in part by the Research Fund of the University of Istanbul. Project number: 513/05052006.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/ISIE.2007.4374868
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBandwidthen_US
dc.subjectBayesian estimationsen_US
dc.subjectBayesian methodsen_US
dc.subjectBayesian networksen_US
dc.subjectChlorine compoundsen_US
dc.subjectCluster based sensor schedulingen_US
dc.subjectCluster baseden_US
dc.subjectClustering algorithmsen_US
dc.subjectClutter (information theory)en_US
dc.subjectCostsen_US
dc.subjectData engineeringen_US
dc.subjectDensity filteren_US
dc.subjectElectronics industryen_US
dc.subjectFiltering theoryen_US
dc.subjectIndustrial electronicsen_US
dc.subjectIntelligent sensorsen_US
dc.subjectInternational symposiumen_US
dc.subjectMaster-slaveen_US
dc.subjectMulti sensorsen_US
dc.subjectMulti-sensor applicationsen_US
dc.subjectNon linearitiesen_US
dc.subjectNon-linearen_US
dc.subjectNonlinear Bayesian estimationen_US
dc.subjectOF sensorsen_US
dc.subjectParameter estimationen_US
dc.subjectParticle filteringen_US
dc.subjectPattern clusteringen_US
dc.subjectProcessor schedulingen_US
dc.subjectProduction controlen_US
dc.subjectSchedulingen_US
dc.subjectSensor fusionen_US
dc.subjectSensor phenomena and characterizationen_US
dc.subjectSensor managementen_US
dc.subjectSensor schedulingen_US
dc.subjectSensorsen_US
dc.subjectSignal filtering and predictionen_US
dc.subjectTarget trackingen_US
dc.subjectTarget tracking applicationen_US
dc.subjectTechnical presentationsen_US
dc.titleCluster based sensor scheduling in a target tracking application with particle filteringen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisher's Versionen_US
dc.relation.journal2007 IEEE International Symposium on Industrial Electronics, Proceedings, Vols 1-8en_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.contributor.authorID0000-0001-6556-4104
dc.identifier.startpage1741
dc.identifier.endpage1746
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorBayazıt, Uluğen_US


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