Wolf Lyapunov exponent estimation from a time series.

Version 1.2.0.1 (2,39 Mo) par Alan Wolf
A Matlab version of the Lyapunov exponent estimation algorithm of Wolf et al. -- Physica 16D, 1985.
4.8
(40)
10,4K téléchargements
Mise à jour 14 août 2019

Afficher la licence

In Physica 16D (1985) we presented an algorithm that estimates the dominant Lyapunov exponent of a 1-D time series by monitoring orbital divergence. The algorithm was distributed for many years by the authors in Fortran and C. It has just been converted to Matlab. Documentation is included (both the Physica D article, and a pdf named Lyapunews).

The sample files I included were written as unix newline terminated data points. These files may look strange when displayed by various editors. Feel free to create data files with any software that can output time series values, one per line, terminated with a carriage return AND line feed. The existing code will read such files in perfectly well.

If you have questions, PLEASE DON'T POST THEM HERE. Please write me directly at the email address contained in this download: awolf.physics@gmail.com

Citation pour cette source

Alan Wolf (2024). Wolf Lyapunov exponent estimation from a time series. (https://www.mathworks.com/matlabcentral/fileexchange/48084-wolf-lyapunov-exponent-estimation-from-a-time-series), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2014b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Catégories
En savoir plus sur Matrix Computations dans Help Center et MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version Publié le Notes de version
1.2.0.1

Corrected description -- documentation IS included. Addressed formatting of input files. Provided an email address so questions can be sent to me directly.
1.2.0.0

clarified meaning of EVOLVE parameter.
Documentation added on 3/16/16
1.1.0.0

10/12/14 -- Added some notes to "documentation.txt" which will probably be sufficient for those who have already used the algorithm. More detailed notes to follow within a week.
1.0.0.0