Dynamical system analysis of a data-driven model constructed by reservoir computing
Author:
Funder
Japan Society for the Promotion of Science
Kyoto University
Publisher
American Physical Society (APS)
Link
http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevE.104.044215/fulltext
Reference27 articles.
1. An experimental unification of reservoir computing methods
2. Reservoir observers: Model-free inference of unmeasured variables in chaotic systems
3. Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
4. Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach
5. Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography
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2. Attractor reconstruction with reservoir computers: The effect of the reservoir’s conditional Lyapunov exponents on faithful attractor reconstruction;Chaos: An Interdisciplinary Journal of Nonlinear Science;2024-04-01
3. Constructing low-dimensional ordinary differential equations from chaotic time series of high- or infinite-dimensional systems using radial-function-based regression;Physical Review E;2023-11-22
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