DC FieldValueLanguage
dc.contributor.authorTodorović, Branimiren
dc.contributor.authorStanković, Miomiren
dc.contributor.authorTodorović-Zarkula, Slavicaen
dc.date.accessioned2020-12-11T13:04:42Z-
dc.date.available2020-12-11T13:04:42Z-
dc.date.issued2000-12-01en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/4422-
dc.description.abstractSequential adaptation of RBF network parameters and structure is achieved using extended Kalman filter. Criterion for network growing is obtained from Kalman filter's consistency test. The Optimal Brain Surgeon and Optimal Brain Damage prunning methods are derived for networks which parameters are estimated by EKF. Criteria for neurons/connections pruning are based on the statistical parameter significance test.en
dc.publisherIEEE-
dc.relation.ispartofProceedings of the Mediterranean Electrotechnical Conference - MELECONen
dc.titleOn-line adaptive RBF network in stationary and nonstationary environmenten
dc.typeConference Paperen
dc.relation.conference10th Mediterranean Electrotechnical Conference (MALECON2000); Lemesos, Cyprus ; 29 May 2000 through 31 May 2000-
dc.identifier.doi10.1109/MELCON.2000.879968-
dc.identifier.scopus2-s2.0-0034482360en
dc.relation.firstpage453en
dc.relation.lastpage456en
dc.relation.volume2en
dc.description.rankM33-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Paper-
item.grantfulltextnone-
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