Statistical models of reconstructed phase spaces for signal classification

  title={Statistical models of reconstructed phase spaces for signal classification},
  author={Richard J. Povinelli and Michael T. Johnson and Andrew C. Lindgren and Felice M. Roberts and Jinjin Ye},
  journal={IEEE Transactions on Signal Processing},
This paper introduces a novel approach to the analysis and classification of time series signals using statistical models of reconstructed phase spaces. With sufficient dimension, such reconstructed phase spaces are, with probability one, guaranteed to be topologically equivalent to the state dynamics of the generating system, and, therefore, may contain information that is absent in analysis and classification methods rooted in linear assumptions. Parametric and nonparametric distributions are… CONTINUE READING
Highly Cited
This paper has 65 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 32 extracted citations

66 Citations

Citations per Year
Semantic Scholar estimates that this publication has 66 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 36 references


  • T. Sauer, J. A. Yorke, M. Casdagli
  • J. Stat. Phys., vol. 65, pp. 579–616, 1991.
  • 1991
Highly Influential
3 Excerpts

Quantitative Cardiac Electrophysiology

  • C. Cabo, D. S. Rosenbaum
  • 2002

Similar Papers

Loading similar papers…