Consistency Hierarchy of Reservoir Computers.
IEEE Trans Neural Netw Learn Syst
; 33(6): 2586-2595, 2022 Jun.
Article
em En
| MEDLINE
| ID: mdl-34695007
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.
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2022
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Article