Predictability: a way to characterize Complexity (Articolo in rivista)

Type
Label
  • Predictability: a way to characterize Complexity (Articolo in rivista) (literal)
Anno
  • 2002-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/S0370-1573(01)00025-4 (literal)
Alternative label
  • Boffetta G., Cencini M., Falcioni M., Vulpiani A. (2002)
    Predictability: a way to characterize Complexity
    in Physics Reports. A review section of physics letters
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Boffetta G., Cencini M., Falcioni M., Vulpiani A. (literal)
Pagina inizio
  • 367 (literal)
Pagina fine
  • 474 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 356 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • a Dipartimento di Fisica Generale, Universita di Torino, Via Pietro Giuria 1, I-10125 Torino, Italy ? b Istituto Nazionale Fisica della Materia, Unita dell'Universit ? a di Torino, Italy ? c Max-Planck-Institut fur Physik komplexer Systeme, N ' othnitzer Str. 38, 01187 Dresden, Germany ' dDipartimento di Fisica, Universita di Roma \"la Sapienza\", Piazzale Aldo Moro 5, 00185 Roma, Italy ? e Istituto Nazionale Fisica della Materia, Unita di Roma 1, Italy (literal)
Titolo
  • Predictability: a way to characterize Complexity (literal)
Abstract
  • Different aspects of the predictability problem in dynamical systems are reviewed. The deep relation among Lyapunov exponents, Kolmogorov-Sinai entropy, Shannon entropy and algorithmic complexity is discussed. In particular, we emphasize how a characterization of the unpredictability of a system gives a measure of its complexity. Adopting this point of view, we review some developments in the characterization of the predictability of systems showing different kind of complexity: from low-dimensional systems to high-dimensional ones with spatio-temporal chaos and to fully developed turbulence. A special attention is devoted to finite-time and finite-resolution effects on predictability, which can be accounted with suitable generalization of the standard indicators. The problems involved in systems with intrinsic randomness is discussed, with emphasis on the important problems of distinguishing chaos from noise and of modeling the system. The characterization of irregular behavior in systems with discrete phase space is also considered. (literal)
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