Recovery of hidden macroscopic signals in a Kuramoto phase oscillators network

We are solving the task of recovering the hidden signals in a model network. As a model we choose Kuramoto phase oscillator with adaptation of couplings. We divide the network for six parts and calculate macroscopic signals. We propose that knowing only a part of macroscopic signals allows us to recover the rest unknown ones. We show that using Reservoir computing successfully solves the problem.