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Using method of artificial intelligence to estimate parameters of chaotic synchronization systems

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dc.title Using method of artificial intelligence to estimate parameters of chaotic synchronization systems en
dc.contributor.author Nguyen, Thanh Dung
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof MENDEL 2011
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-80-214-4302-0
dc.date.issued 2011
utb.relation.volume 2011
dc.citation.spage 22
dc.citation.epage 29
dc.event.title 17th International Conference on Soft Computing MENDEL 2011
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2011-06-15
dc.event.edate 2011-06-17
dc.type conferenceObject
dc.language.iso en
dc.publisher Vysoké učení technické v Brně cs
dc.subject Chaos theory en
dc.subject secure communication en
dc.subject identical synchronization en
dc.subject self-organizing migrating algorithm en
dc.subject differential evolution algorithm en
dc.subject Lotka-Volterra chaos system en
dc.subject Pecora and Carroll method en
dc.description.abstract This paper aims to present the combination of chaotic signal and evolutionary algorithms to estimate the unknown parameters in chaos synchronization system via the Pecora and Carroll method. The self-organizing migrating algorithm (SOMA) and Differential Evolution (DE) were used to estimate the unknown parameters. Based on the results from evolutionary algorithms, two identical chaotic systems were synchronized. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1002808
utb.identifier.rivid RIV/70883521:28140/11:43868166!RIV13-MSM-28140___
utb.identifier.obdid 43868259
utb.identifier.scopus 2-s2.0-84904192818
utb.identifier.wok 000302647900004
utb.source d-wok
dc.date.accessioned 2012-06-04T11:34:11Z
dc.date.available 2012-06-04T11:34:11Z
utb.contributor.internalauthor Nguyen, Thanh Dung
utb.contributor.internalauthor Zelinka, Ivan
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