Reconstruction of Complex Dynamical Systems from Time Series using Reservoir Computing
Thomas Jüngling, Thomas Lymburn, Thomas Stemler, Débora Corrêa, David M. Walker, MICHAEL P. SMALL · 2019
We investigate the capacity of reservoir computers to reconstruct the dynamics of a network of chaotic oscillators via the observation of its multivariate time series. The reservoir is itself a structured echo-state network which receives the current observations as inputs, and is trained to produce the next observations as outputs. We study the performance of this scheme and its dependence on the separation of the inputs, modularity of the reservoir network, and observability of the system. We observe optimal performance with a segregated input structure and extremely modular network.