Local dimension and finite time prediction in spatiotemporal chaotic systems.
Phys Rev E Stat Nonlin Soft Matter Phys
; 67(6 Pt 2): 066204, 2003 Jun.
Article
em En
| MEDLINE
| ID: mdl-16241323
We show how a recently introduced statistic [Patil et al., Phys. Rev. Lett. 81, 5878 (2001)] provides a direct relationship between dimension and predictability in spatiotemporal chaotic systems. Regions of low dimension are identified as having high predictability and vice versa. This conclusion is reached by using methods from dynamical systems theory and Bayesian modeling. In this work we emphasize on the consequences for short time forecasting and examine the relevance for factor analysis. Although we concentrate on coupled map lattices and coupled nonlinear oscillators for convenience, any other spatially distributed system could be used instead, such as turbulent fluid flows.
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01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Phys Rev E Stat Nonlin Soft Matter Phys
Assunto da revista:
BIOFISICA
/
FISIOLOGIA
Ano de publicação:
2003
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Estados Unidos