Spatiotemporal chaos control through complexity measures

Navrátil, Eduard; Zelinka, Ivan; Šenkeřík, Roman

dc.title	Spatiotemporal chaos control through complexity measures	en
dc.contributor.author	Navrátil, Eduard
dc.contributor.author	Zelinka, Ivan
dc.contributor.author	Šenkeřík, Roman
dc.relation.ispartof	MENDEL 2006
dc.identifier.issn	1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	80-214-3195-4
dc.date.issued	2006
utb.relation.volume	2006-January
utb.relation.issue	January
dc.citation.spage	68
dc.citation.epage	72
dc.event.title	12th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2006
dc.event.location	Brno
utb.event.state-en	Czech Republic
utb.event.state-cs	Česká republika
dc.event.sdate	2006-05-31
dc.event.edate	2006-06-02
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Brno University of Technology
dc.subject	Complexity measures	en
dc.subject	Coupled map lattices	en
dc.subject	Evolution	en
dc.subject	Mean information gain	en
dc.subject	Mean mutual information	en
dc.subject	Optimization	en
dc.subject	SOMA	en
dc.subject	Spatiotemporal chaos	en
dc.description.abstract	This contribution deals with control of spatiotemporal chaos represented by one-dimensional logistic CML. The pinning value is tuned via the self-organizing migrating algorithm optimization to achieve either stable or periodic state. To accomplish this aim SOMA is given cost functions based on entropy, mean information gain and mean mutual information.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1005249
utb.identifier.obdid	14553388
utb.identifier.scopus	2-s2.0-84937053566
utb.source	d-scopus
dc.date.accessioned	2015-08-14T09:26:19Z
dc.date.available	2015-08-14T09:26:19Z
utb.contributor.internalauthor	Navrátil, Eduard
utb.contributor.internalauthor	Zelinka, Ivan
utb.contributor.internalauthor	Šenkeřík, Roman