Open AccessInformation theory approach to determine embedding parameters for phase space reconstruction of chaotic time series
Author(s) -
Xiao Fang-Hong,
Yan Gui-Rong,
Han Yu-Hang
Publication year - 2005
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.54.550
Subject(s) - embedding , dimension (graph theory) , phase space , chaotic , series (stratigraphy) , computer science , entropy (arrow of time) , mutual information , time series , correlation dimension , intrinsic dimension , algorithm , statistical physics , theoretical computer science , mathematics , mathematical analysis , artificial intelligence , physics , pure mathematics , fractal dimension , machine learning , quantum mechanics , paleontology , biology , fractal , curse of dimensionality
We have studied the determination of delay time and embedding dimension for phase space reconstruction of chaotic time series using the information theory. We use the symbolic analysis method to compute mutual information for determining the delay time. Furthermore we also present an information theory approach to determine embedding dimension. That is, we determine the embedding dimension by considering the variation of the conditional entropy of the reconstructed vector with its dimension. Numerical simulations verify that the method is applicable for determining an appropriate embedding dimension.