Local Lyapunov Exponents: A new way to predict chaotic systems

Dominique Guegan () and Justin Leroux
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Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Justin Leroux: HEC Montréal - HEC Montréal

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Abstract: We propose a novel methodology for forecasting chaotic systems which is based on exploiting the information conveyed by the local Lyapunov ex- ponent of a system. We show how our methodology can improve forecast- ing within the attractor and illustrate our results on the Lorenz system.

Keywords: Lyapunov exponent; Chaos; Forecasting (search for similar items in EconPapers)
Date: 2009-06
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00511996v1
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Citations: View citations in EconPapers (3)

Published in Christos H. Skiadas, Ioannis Dimotikalis, Charilaos Skiadas. Topics on Chaotic Systems: Selected papers from CHAOS 2008, International Conference, World Scientific Publishing, pp.158-185, 2009

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