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postgraduate thesis: On-line fault diagnosis of nonlinear dynamical systems using recurrentneural networks

TitleOn-line fault diagnosis of nonlinear dynamical systems using recurrentneural networks
Authors
Issue Date2000
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Wang, Y. [王鷹]. (2000). On-line fault diagnosis of nonlinear dynamical systems using recurrent neural networks. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3124238
DegreeDoctor of Philosophy
SubjectFault location (Engineering)
Nonlinear systems.
Neural networks (Computer science)
Dept/ProgramMechanical Engineering

 

DC FieldValueLanguage
dc.contributor.authorWang, Ying-
dc.contributor.author王鷹-
dc.date.issued2000-
dc.identifier.citationWang, Y. [王鷹]. (2000). On-line fault diagnosis of nonlinear dynamical systems using recurrent neural networks. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3124238-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.source.urihttp://hub.hku.hk/bib/B31242388-
dc.subject.lcshFault location (Engineering)-
dc.subject.lcshNonlinear systems.-
dc.subject.lcshNeural networks (Computer science)-
dc.titleOn-line fault diagnosis of nonlinear dynamical systems using recurrentneural networks-
dc.typePG_Thesis-
dc.identifier.hkulb3124238-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineMechanical Engineering-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b3124238-
dc.date.hkucongregation2001-

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