Publicação: Local dimension and finite time prediction in spatiotemporal chaotic systems
dc.contributor.author | Francisco, Gerson [UNESP] | |
dc.contributor.author | Muruganandam, Paulsamy [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.contributor.institution | Bharathidasan University | |
dc.date.accessioned | 2014-05-27T11:20:40Z | |
dc.date.available | 2014-05-27T11:20:40Z | |
dc.date.issued | 2003-06-01 | |
dc.description.abstract | Predictability 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.affiliation | Instituto de Fisica Teorica Universidade Estadual Paulista, 01405-900 Sao Paulo, SP | |
dc.description.affiliation | Center for Nonlinear Dynamics Department of Physics Bharathidasan University, Tiruchirapalli 620024, Tamil Nadu | |
dc.description.affiliationUnesp | Instituto de Fisica Teorica Universidade Estadual Paulista, 01405-900 Sao Paulo, SP | |
dc.identifier | http://dx.doi.org/10.1103/PhysRevE.67.066204 | |
dc.identifier.citation | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003. | |
dc.identifier.doi | 10.1103/PhysRevE.67.066204 | |
dc.identifier.file | 2-s2.0-42749108043.pdf | |
dc.identifier.issn | 1063-651X | |
dc.identifier.scopus | 2-s2.0-42749108043 | |
dc.identifier.uri | http://hdl.handle.net/11449/67300 | |
dc.identifier.wos | WOS:000184085000038 | |
dc.language.iso | eng | |
dc.relation.ispartof | Physical Review E: Statistical, Nonlinear, and Soft Matter Physics | |
dc.rights.accessRights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Algorithms | |
dc.subject | Boundary conditions | |
dc.subject | Eigenvalues and eigenfunctions | |
dc.subject | Forecasting | |
dc.subject | Matrix algebra | |
dc.subject | Probability | |
dc.subject | Probability distributions | |
dc.subject | Random processes | |
dc.subject | Statistical methods | |
dc.subject | Vectors | |
dc.subject | Bayesian modeling | |
dc.subject | Dynamical systems theory | |
dc.subject | Finite time prediction | |
dc.subject | Local dimension | |
dc.subject | Spatiotemporal chaotic system | |
dc.subject | Chaos theory | |
dc.title | Local dimension and finite time prediction in spatiotemporal chaotic systems | en |
dc.type | Artigo | |
dcterms.license | http://publish.aps.org/authors/transfer-of-copyright-agreement | |
dspace.entity.type | Publication | |
unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulo | pt |
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