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Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/732
DC FieldValueLanguage
dc.contributor.authorDagher, Issamen_US
dc.contributor.authorGeorgiopoulos, Men_US
dc.contributor.authorHeileman, G.Len_US
dc.contributor.authorBebis, Gen_US
dc.date.accessioned2020-12-23T08:35:49Z-
dc.date.available2020-12-23T08:35:49Z-
dc.date.issued2002-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/732-
dc.description.abstractIn this paper we introduce a procedure that identifies a fixed order of training pattern presentation for fuzzy ARTMAP. The resulting algorithm is named ordered fuzzy ARTMAP. Experimental results have demonstrated that ordered fuzzy ARTMAP achieves a network performance that is better than the average fuzzy ARTMAP network performance (averaged over a fixed number of random orders of pattern presentations), and occasionally better than the maximum fuzzy ARTMAP network performance (maximum over a fixed number of random orders of pattern presentations). What is also worth noting is that the computational complexity of the aforementioned procedure is only a small fraction of the computational complexity required to complete the training phase of fuzzy ARTMAP for a single order of pattern presentation.en_US
dc.format.extent6 p.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.subjectPattern classificationen_US
dc.subjectFuzzy neural netsen_US
dc.subjectART neural netsen_US
dc.subject.lcshComputational complexityen_US
dc.titleOrdered fuzzy ARTMAPen_US
dc.typeConference Paperen_US
dc.relation.conferenceIEEE International Joint Conference on Neural Networks (4-9 May 1998 : Anchorage, AK, USA)en_US
dc.contributor.affiliationDepartment of Computer Engineeringen_US
dc.description.startpage1717en_US
dc.description.endpage1722en_US
dc.date.catalogued2018-02-21-
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://ieeexplore.ieee.org/abstract/document/687115/en_US
dc.identifier.OlibID177926-
dc.relation.ispartoftextIEEE World Congress on Computational Intelligence. IEEE International Joint Conference on Neural Networks Proceedingsen_US
dc.provenance.recordsourceOliben_US
crisitem.author.parentorgFaculty of Engineering-
Appears in Collections:Department of Computer Engineering
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