Consistency Hierarchy of Reservoir Computers
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 cap...
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Veröffentlicht in: | IEEE transaction on neural networks and learning systems 2022-06, Vol.33 (6), p.2586-2595 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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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ISSN: | 2162-237X 2162-2388 |
DOI: | 10.1109/TNNLS.2021.3119548 |