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Entropy 2018, 20(11), 891; https://doi.org/10.3390/e20110891

Improving Entropy Estimates of Complex Network Topology for the Characterization of Coupling in Dynamical Systems

1
National Institute for Laser, Plasma and Radiation Physics, RO-077125 Magurele-Bucharest, Romania
2
Consorzio RFX (CNR, ENEA, INFN, Universita’ di Padova, Acciaierie Venete SpA), 35127 Padova, Italy
3
EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB, UK
4
Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
Received: 24 October 2018 / Revised: 13 November 2018 / Accepted: 19 November 2018 / Published: 20 November 2018
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Abstract

A new measure for the characterization of interconnected dynamical systems coupling is proposed. The method is based on the representation of time series as weighted cross-visibility networks. The weights are introduced as the metric distance between connected nodes. The structure of the networks, depending on the coupling strength, is quantified via the entropy of the weighted adjacency matrix. The method has been tested on several coupled model systems with different individual properties. The results show that the proposed measure is able to distinguish the degree of coupling of the studied dynamical systems. The original use of the geodesic distance on Gaussian manifolds as a metric distance, which is able to take into account the noise inherently superimposed on the experimental data, provides significantly better results in the calculation of the entropy, improving the reliability of the coupling estimates. The application to the interaction between the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole and to the influence of ENSO on influenza pandemic occurrence illustrates the potential of the method for real-life problems. View Full-Text
Keywords: system coupling; cross-visibility graphs; image entropy; geodesic distance system coupling; cross-visibility graphs; image entropy; geodesic distance
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Craciunescu, T.; Murari, A.; Gelfusa, M. Improving Entropy Estimates of Complex Network Topology for the Characterization of Coupling in Dynamical Systems. Entropy 2018, 20, 891.

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