Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Nonlinear Sciences > Chaotic Dynamics

arXiv:nlin/0307013 (nlin)
[Submitted on 7 Jul 2003]

Title:Complexity Characterization of Dynamical Systems Through Predictability

Authors:Fabio Cecconi, Massimo Falcioni, Angelo Vulpiani
View PDF
Abstract: Some 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.
Comments: 26 pages, 5 eps-figures, Presented at the XV Marian Smoluchowski Symposium on Statistical Physics, Zakopane (Poland), Sept. 2002
Subjects: Chaotic Dynamics (nlin.CD)
Cite as: arXiv:nlin/0307013 [nlin.CD]
  (or arXiv:nlin/0307013v1 [nlin.CD] for this version)
  https://doi.org/10.48550/arXiv.nlin/0307013
Journal reference: Acta Physica Polonica, vol.34, pag.3851 (2003)

Submission history

From: F. Cecconi [view email]
[v1] Mon, 7 Jul 2003 15:41:09 UTC (60 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
nlin.CD
< prev   |   next >
new | recent | 2003-07

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)