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[00456] Network representations of attractors for surrogates generation and change detection

  • Session Time & Room : 2E (Aug.22, 17:40-19:20) @G709
  • Type : Contributed Talk
  • Abstract : Attractors arising from delay embedded time-series can characterise system dynamics. However, extracting useful representations is challenging for systems with high-dimensional or complex structure. We propose a data-driven method to represent attractors as networks, where dynamics are encoded as node transition probabilities. The usefulness of this representation is demonstrated in two tasks: (1) surrogate data generation; and (2) change point detection. These methods are applied to chaotic time-series, and experimental ECG data for heart attack detection.
  • Classification : 37M10, 37M22, 94C12
  • Format : Talk at Waseda University
  • Author(s) :
    • Eugene Tan (The University of Western Australia)
    • Shannon Dee Algar (The University of Western Australia)
    • Debora Correa (The University of Western Australia)
    • Thomas Stemler (The University of Western Australia)
    • Michael Small (The University of Western Australia)