Detection of time delays and directional interactions based on time series from complex dynamical systems

Huanfei Ma, Siyang Leng, Chenyang Tao, Xiong Ying, Jürgen Kurths, Ying-Cheng Lai, and Wei Lin
Phys. Rev. E 96, 012221 – Published 25 July 2017

Abstract

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30–40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

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  • Received 29 December 2016
  • Revised 28 June 2017

DOI:https://doi.org/10.1103/PhysRevE.96.012221

©2017 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Physics of Living SystemsNonlinear Dynamics

Authors & Affiliations

Huanfei Ma1,2, Siyang Leng2,3, Chenyang Tao2,3, Xiong Ying2,3, Jürgen Kurths4,5, Ying-Cheng Lai5,6, and Wei Lin2,3,*

  • 1School of Mathematical Sciences, Soochow University, Suzhou 215006, China
  • 2Centre for Computational Systems Biology of ISTBI, Fudan University, Shanghai 200433, China
  • 3School of Mathematical Sciences and SCMS, Fudan University, Shanghai 200433, China
  • 4Potsdam Institute for Climate Impact Research, D-14412 Potsdam, and Department of Physics, Humboldt University of Berlin, D-12489 Berlin, Germany
  • 5Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom
  • 6School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85287-5706, USA

  • *wlin@fudan.edu.cn

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Issue

Vol. 96, Iss. 1 — July 2017

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