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dc.contributor.authorBarshan, B.en_US
dc.contributor.authorAyrulu, B.en_US
dc.date.accessioned2016-02-08T10:27:40Z
dc.date.available2016-02-08T10:27:40Z
dc.date.issued2004en_US
dc.identifier.issn0031-3203
dc.identifier.urihttp://hdl.handle.net/11693/24327
dc.description.abstractThe fuzzy c-means (FCM) clustering algorithm is used in conjunction with a cluster validity criterion, to determine the number of different types of targets in a given environment, based on their sonar signatures. The class of each target and its location are also determined. The method is experimentally verified using real sonar returns from targets in indoor environments. A correct differentiation rate of 98% is achieved with average absolute valued localization errors of 0.5 cm and 0.8° in range and azimuth, respectively.en_US
dc.language.isoEnglishen_US
dc.source.titlePattern Recognitionen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/S0031-3203(03)00226-7en_US
dc.subjectFuzzy c-means clusteringen_US
dc.subjectSonar sensingen_US
dc.subjectTarget classificationen_US
dc.subjectTarget differentiationen_US
dc.subjectTarget localizationen_US
dc.subjectAlgorithmsen_US
dc.subjectSonaren_US
dc.subjectEnumerationen_US
dc.subjectFuzzy clusteringen_US
dc.subjectFuzzy setsen_US
dc.titleFuzzy clustering and enumeration of target type based on sonar returnsen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage189en_US
dc.citation.epage199en_US
dc.citation.volumeNumber37en_US
dc.citation.issueNumber2en_US
dc.identifier.doi10.1016/S0031-3203(03)00226-7en_US
dc.publisherElsevieren_US


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