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Conference Paper: Development of an embedded fuzzy-based replication technique for chaotic system

TitleDevelopment of an embedded fuzzy-based replication technique for chaotic system
Authors
KeywordsAdaptive Systems
Algorithms
Chaos Theory
Mathematical Models
Membership Functions
Neural Networks
Nonlinear Systems
Phase Space Methods
Random Processes
Time Series Analysis
Issue Date1999
PublisherIEEE
Citation
Canadian Conference On Electrical And Computer Engineering, 1999, v. 2, p. 1029-1034 How to Cite?
AbstractThis paper addresses an embedded Fuzzy-based replication technique for chaotic dynamic system. It hybridizes the advantages of Fuzzy Logic that is capable of handling complex, nonlinear and sometimes mathematically intangible dynamic systems and the global modeling capability of embedding phase space. The methodology is based on the fundamental characteristics of chaotic time series, which exhibits some stochastic behavior in time domain and its deterministic behavior can be displayed in the embedding phase space. For a given chaotic time series, an embedding phase space is firstly reconstructed by selecting same appropriate phase space points, the membership function in the fuzzy system will be optimized by using a back-propagation adaptive neural-fuzzy system. The proposed method is demonstrated by an example of Mackey-grass chaotic equation. The repredicted time series are favorably compared to the calculated one.
Persistent Identifierhttp://hdl.handle.net/10722/136845
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhang, Junen_HK
dc.contributor.authorChung, Henryen_HK
dc.contributor.authorHui, SYRen_HK
dc.date.accessioned2011-07-29T02:13:06Z-
dc.date.available2011-07-29T02:13:06Z-
dc.date.issued1999en_HK
dc.identifier.citationCanadian Conference On Electrical And Computer Engineering, 1999, v. 2, p. 1029-1034en_HK
dc.identifier.issn0840-7789en_HK
dc.identifier.urihttp://hdl.handle.net/10722/136845-
dc.description.abstractThis paper addresses an embedded Fuzzy-based replication technique for chaotic dynamic system. It hybridizes the advantages of Fuzzy Logic that is capable of handling complex, nonlinear and sometimes mathematically intangible dynamic systems and the global modeling capability of embedding phase space. The methodology is based on the fundamental characteristics of chaotic time series, which exhibits some stochastic behavior in time domain and its deterministic behavior can be displayed in the embedding phase space. For a given chaotic time series, an embedding phase space is firstly reconstructed by selecting same appropriate phase space points, the membership function in the fuzzy system will be optimized by using a back-propagation adaptive neural-fuzzy system. The proposed method is demonstrated by an example of Mackey-grass chaotic equation. The repredicted time series are favorably compared to the calculated one.en_HK
dc.languageengen_US
dc.publisherIEEEen_US
dc.relation.ispartofCanadian Conference on Electrical and Computer Engineeringen_HK
dc.subjectAdaptive Systemsen_US
dc.subjectAlgorithmsen_US
dc.subjectChaos Theoryen_US
dc.subjectMathematical Modelsen_US
dc.subjectMembership Functionsen_US
dc.subjectNeural Networksen_US
dc.subjectNonlinear Systemsen_US
dc.subjectPhase Space Methodsen_US
dc.subjectRandom Processesen_US
dc.subjectTime Series Analysisen_US
dc.titleDevelopment of an embedded fuzzy-based replication technique for chaotic systemen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailHui, SYR:ronhui@eee.hku.hken_HK
dc.identifier.authorityHui, SYR=rp01510en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0033326155en_HK
dc.identifier.volume2en_HK
dc.identifier.spage1029en_HK
dc.identifier.epage1034en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridZhang, Jun=35239357700en_HK
dc.identifier.scopusauthoridChung, Henry=7404007467en_HK
dc.identifier.scopusauthoridHui, SYR=7202831744en_HK

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