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Fig. 4 Predicting response patterns of fluctuation-driven networks.

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Presentation on theme: "Fig. 4 Predicting response patterns of fluctuation-driven networks."— Presentation transcript:

1 Fig. 4 Predicting response patterns of fluctuation-driven networks.
Predicting response patterns of fluctuation-driven networks. (A) A noisy signal Fi (purple) at one unit and (B) frequency response dθi/dt at another unit in the network (Fig. 1A), with every unit driven by independent Brownian noise. (B) Response prediction (black) is based on 50 dominant Fourier modes of the signal [reconstructing the yellow time series in (A)] at each unit, which, after a transient stage, is very close to the numerical response (purple) to the original signals. (C) Prediction error E (for definition, see Materials and Methods) decreases exponentially with the number of selected Fourier modes. (D) Linear response theory well predicts responses until the maximum line load exceeds 95% (line load Lij ≔ ∣sin(θj − θi)∣), i.e., the system is almost fully loaded at the operating point. Xiaozhu Zhang et al. Sci Adv 2019;5:eaav1027 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

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