Most probable dimension value and most flat interval methods for automatic estimation of dimension from time series

DOI10.1016/j.chaos.2003.08.012zbMath1048.37071OpenAlexW1970718094MaRDI QIDQ1878105

Angelo Corana, Aldo Casaleggio, Giovanni Bortolan

Publication date: 19 August 2004

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2003.08.012

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10) Dimension theory of smooth dynamical systems (37C45)

Related Items (2)

Attractor reconstruction of self-excited mechanical systems ⋮ Using scaling-region distributions to select embedding parameters

Uses Software

• PhysioToolkit

Cites Work

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• There is a theory of heart
• Measuring the strangeness of strange attractors
• Extracting qualitative dynamics from experimental data
• Efficient computation of the correlation dimension from a time series on a LIW computer
• Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems
• Embedology
• Estimating correlation dimension from a chaotic time series: When does plateau onset occur?
• Using the pointwise dimension to filter time series.
• A posteriori tests to validate dimension estimates from time series
• Automatic estimation of the correlation dimension for the analysis of electrocardiograms
• The influence of noise on the correlation dimension of chaotic attractors
• Independent coordinates for strange attractors from mutual information
• STATISTICAL ERROR IN A CHORD ESTIMATOR OF CORRELATION DIMENSION: THE “RULE OF FIVE”

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