World Scientific
  • Search
  •   
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.

CHAOTIC INDICATORS AND GAUSSIAN RANDOM PROCESSES: SOME SURPRISING RESULTS

    https://doi.org/10.1142/S0218348X96000108Cited by:1 (Source: Crossref)

    The search for low-dimensional chaos in ocean surface waves is nowadays a very active field. The interpretation of the results, however, is not always straightforward. The issue addressed in this paper is how time series analysis tools from dynamical systems theory behave for a class of Gaussian processes often used in the study of ocean surface waves. The study includes the largest Lyapunov exponent, the Grassberger and Procaccia correlation dimension and the self-similarity properties. Surprisingly, for certain parameter ranges, the correlation dimension is found to be finite, the largest Lyapunov exponent is found to be positive and structure appears on all time scales. These results suggest that improved techniques and data analysis procedures may be required in order to study chaos properties of ocean surface waves or of other Gaussian processes with similar power spectra.

    Remember to check out the Most Cited Articles!

    Check out New & Notable Titles in Nonlinear Science
    Includes authors Leon O Chua, Bruce J West and more

    "