Consistency Hierarchy of Reservoir Computers

IEEE Trans Neural Netw Learn Syst. 2022 Jun;33(6):2586-2595. doi: 10.1109/TNNLS.2021.3119548. Epub 2022 Jun 1.

Abstract

We study the propagation and distribution of information-carrying signals injected in dynamical systems serving as reservoir computers. Through different combinations of repeated input signals, a multivariate correlation analysis reveals measures known as the consistency spectrum and consistency capacity. These are high-dimensional portraits of the nonlinear functional dependence between input and reservoir state. For multiple inputs, a hierarchy of capacities characterizes the interference of signals from each source. For an individual input, the time-resolved capacities form a profile of the reservoir's nonlinear fading memory. We illustrate this methodology for a range of echo state networks.