Document Type
Article
Version
Publisher's PDF
Publication Title
Physical Review A
Volume
38
Publication Date
9-15-1988
Abstract
A singular-value decomposition leads to a set of statistically independent variables which are used in the Grassberger-Procaccia algorithm to calculate the correlation dimension of an attractor from a scalar time series. This combination alleviates some of the difficulties associated with each technique when used alone, and can significantly reduce the computational cost of estimating correlation dimensions from a time series.
Publisher's Statement
© 1988 by the American Physical Society. The publisher's version of the article can be found at http://link.aps.org/doi/10.1103/PhysRevA.38.3017.
Citation
A.M. Albano et al. Phys. Rev. A 38, 3017 (1988).
DOI
10.1103/PhysRevA.38.3017