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dc.contributor.authorChao, CTen_US
dc.contributor.authorTeng, CCen_US
dc.date.accessioned2014-12-08T15:02:47Z-
dc.date.available2014-12-08T15:02:47Z-
dc.date.issued1996-03-01en_US
dc.identifier.issn0020-7721en_US
dc.identifier.urihttp://hdl.handle.net/11536/1414-
dc.description.abstractIn this paper we construct a discrete extended Kalman filter by using fuzzy neural networks. The constructed filter makes it possible to estimate the states of a nonlinear dynamic system with unknown plant model. The unknown plant is identified by a fuzzy neural network that avoids the occurrence of divergence in state estimation. A computer simulation is presented to illustrate the performance and application of the proposed filter.en_US
dc.language.isoen_USen_US
dc.titleA fuzzy neural network based extended Kalman filteren_US
dc.typeArticleen_US
dc.identifier.journalINTERNATIONAL JOURNAL OF SYSTEMS SCIENCEen_US
dc.citation.volume27en_US
dc.citation.issue3en_US
dc.citation.spage333en_US
dc.citation.epage339en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:A1996UJ69700008-
dc.citation.woscount5-
顯示於類別:期刊論文