Incremental Learning Framework for Function Approximation via Combining Mixture of Expert Model and Adaptive Resonance Theory

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dc.contributor.authorKim, Cheol-Tackko
dc.contributor.authorLee, Ju-Jangko
dc.date.accessioned2013-03-27T01:32:16Z-
dc.date.available2013-03-27T01:32:16Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2007-08-05-
dc.identifier.citation2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007, pp.3486 - 3491-
dc.identifier.urihttp://hdl.handle.net/10203/157894-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleIncremental Learning Framework for Function Approximation via Combining Mixture of Expert Model and Adaptive Resonance Theory-
dc.typeConference-
dc.identifier.wosid000251178104058-
dc.identifier.scopusid2-s2.0-37049002415-
dc.type.rimsCONF-
dc.citation.beginningpage3486-
dc.citation.endingpage3491-
dc.citation.publicationname2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007-
dc.identifier.conferencecountryCC-
dc.identifier.conferencelocationHarbin-
dc.contributor.localauthorLee, Ju-Jang-
dc.contributor.nonIdAuthorKim, Cheol-Tack-
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EE-Conference Papers(학술회의논문)
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