Local dimension and finite time prediction in spatiotemporal chaotic systems

Página do item simplificado
dc.contributor.authorFrancisco, Gerson [UNESP]
dc.contributor.authorMuruganandam, Paulsamy [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionBharathidasan University
dc.date.accessioned2014-05-27T11:20:40Z
dc.date.available2014-05-27T11:20:40Z
dc.date.issued2003-06-01
dc.description.abstractPredictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.en
dc.description.affiliationInstituto de Fisica Teorica Universidade Estadual Paulista, 01405-900 Sao Paulo, SP
dc.description.affiliationCenter for Nonlinear Dynamics Department of Physics Bharathidasan University, Tiruchirapalli 620024, Tamil Nadu
dc.description.affiliationUnespInstituto de Fisica Teorica Universidade Estadual Paulista, 01405-900 Sao Paulo, SP
dc.identifierhttp://dx.doi.org/10.1103/PhysRevE.67.066204
dc.identifier.citationPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003.
dc.identifier.doi10.1103/PhysRevE.67.066204
dc.identifier.file2-s2.0-42749108043.pdf
dc.identifier.issn1063-651X
dc.identifier.scopus2-s2.0-42749108043
dc.identifier.urihttp://hdl.handle.net/11449/67300
dc.identifier.wosWOS:000184085000038
dc.language.isoeng
dc.relation.ispartofPhysical Review E: Statistical, Nonlinear, and Soft Matter Physics
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAlgorithms
dc.subjectBoundary conditions
dc.subjectEigenvalues and eigenfunctions
dc.subjectForecasting
dc.subjectMatrix algebra
dc.subjectProbability
dc.subjectProbability distributions
dc.subjectRandom processes
dc.subjectStatistical methods
dc.subjectVectors
dc.subjectBayesian modeling
dc.subjectDynamical systems theory
dc.subjectFinite time prediction
dc.subjectLocal dimension
dc.subjectSpatiotemporal chaotic system
dc.subjectChaos theory
dc.titleLocal dimension and finite time prediction in spatiotemporal chaotic systemsen
dc.typeArtigo
dcterms.licensehttp://publish.aps.org/authors/transfer-of-copyright-agreement
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Física Teórica (IFT), São Paulopt

Arquivos

Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
2-s2.0-42749108043.pdf
Tamanho:
176.29 KB
Formato:
Adobe Portable Document Format
Baixar

Coleções

Artigos - Instituto de Física Teórica (IFT)