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A code to apply reservoir computer to infer short-term causal dependence in a dynamical systems and network links from time-series data
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banerjeeamitava/Reservoir-Computer-Network-Inference
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This is the code to generate results published in the paper "Using machine learning to assess short term causal dependence and infer network links", Chaos 29, 121104 (2019), by Amitava Banerjee, Jaideep Pathak, Rajarshi Roy, Juan G. Restrepo, and Edward Ott, Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 121104 (2019), https://aip.scitation.org/doi/abs/10.1063/1.5134845 Contact Amitava Banerjee at [email protected] or [email protected] for questions or comments. This code uses a reservoir computer to infer network links between coupled Lorenz oscillators from their time-series. The actual code to run is main_code.m. It uses a picture (false.png) to construct the Lorenz network connection pattern from the pixel values and plots the actual and inferred connection patterns side-by-side.
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A code to apply reservoir computer to infer short-term causal dependence in a dynamical systems and network links from time-series data
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