Consistency Hierarchy of Reservoir Computers

Thomas Jungling, Thomas Lymburn, Michael Small

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)2586-2595
Number of pages10
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume33
Issue number6
Early online dateOct 2021
DOIs
Publication statusPublished - 1 Jun 2022

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