Complexity Characterization of Dynamical Systems Through Predictability

dc.creatorCecconi, Fabio
dc.creatorFalcioni, Massimo
dc.creatorVulpiani, Angelo
dc.date2003-07-07
dc.date.accessioned2026-07-07T05:34:51Z
dc.date.available2026-07-07T05:34:51Z
dc.descriptionSome 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. A special attention is devoted to 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.
dc.description26 pages, 5 eps-figures, Presented at the XV Marian Smoluchowski Symposium on Statistical Physics, Zakopane (Poland), Sept. 2002
dc.identifierhttps://arxiv.org/abs/nlin/0307013
dc.identifierhttp://arxiv.org/abs/nlin/0307013
dc.identifierActa Physica Polonica, vol.34, pag.3851 (2003)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/80526
dc.subjectChaotic Dynamics
dc.titleComplexity Characterization of Dynamical Systems Through Predictability
dc.typetext

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