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Calculating Embedding Dimension with Confidence Estimates

  • T. L. CarrollEmail author
  • J. M. Byers
Conference paper
Part of the Understanding Complex Systems book series (UCS)

Abstract

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.US Naval Research Lab, Code 6392Washington, DCUSA
  2. 2.US Naval Research Lab, Code 6395Washington, DCUSA

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