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Spatiotemporal chaos control through complexity measures

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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
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