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

Nguyen, Thanh Dung; Zelinka, Ivan

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