Method for measuring unstable dimension variability from time series

Nick McCullen, Pablo Moresco

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Many of the results in the theory of dynamical systems rely on the assumption of hyperbolicity. One of the possible violations of this condition is the presence of unstable dimension variability (UDV), i.e., the existence in a chaotic attractor of sets of unstable periodic orbits, each with a different number of expanding directions. It has been shown that the presence of UDV poses severe limitations to the length of time for which a numerically generated orbit can be assumed to lie close to a true trajectory of such systems (the shadowing time). In this work we propose a method to detect the presence of UDV in real systems from time series measurements. Variations in the number of expanding directions are detected by determining the local topological dimension of the unstable space for points along a trajectory on the attractor. We show for a physical system of coupled electronic oscillators that with this method it is possible to decompose attractors into subsets with different unstable dimension and from this gain insight into the times a typical trajectory spends in each region.
Original languageEnglish
Pages (from-to)046203
Number of pages10
JournalPhysical Review E (PRE)
Volume73
Issue number4
DOIs
Publication statusPublished - Apr 2006

Keywords

  • nonlinear dynamics
  • chaos

Fingerprint Dive into the research topics of 'Method for measuring unstable dimension variability from time series'. Together they form a unique fingerprint.

Cite this