Network topology reconstructed from derivative-variable correlations

2013/06/11 by Zoran Levnajić, Levnajić, Zoran, Arkady Pikovsky +1
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Statistical Mechanics (cond-mat.stat-mech) #Statistics and Probability (physics.data-an) #cond-mat.stat-mech #physics.data-an

paper · pdf · doi:10.48550/arxiv.1306.2462

arxiv created 2013/10/28 · arxiv updated 2013/10/29

Abstract

A method of network reconstruction from the dynamical time series is introduced, relying on the concept of derivative-variable correlation. Using a tunable observable as a parameter, the reconstruction of any network with known interaction functions is formulated via simple matrix equation. We suggest a procedure aimed at optimizing the reconstruction from the time series of length comparable to the characteristic dynamical time scale. Our method also provides a reliable precision estimate. We illustrate the method's implementation via elementary dynamical models, and demonstrate its robustness to both model and observation errors.

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