Consistency in echo-state networks

Thomas Michael Lymburn; Alexander Joseph Khor; Thomas Stemler; Debora Correa; Michael Small; Thomas Jungling

doi:10.1063/1.5079686

Consistency in echo-state networks

Thomas Michael Lymburn, Alexander Joseph Khor, Thomas Stemler, Debora Correa, Michael Small, Thomas Jungling

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47 Citations (Scopus)

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Abstract

Consistency is an extension to generalized synchronization which quantifies the degree of functional dependency of a driven nonlinear system to its input. We apply this concept to echo-state networks, which are an artificial-neural network version of reservoir computing. Through a replica test, we measure the consistency levels of the high-dimensional response, yielding a comprehensive portrait of the echo-state property.

Original language	English
Article number	023118
Pages (from-to)	1-9
Number of pages	9
Journal	Chaos: an interdisciplinary journal of nonlinear science
Volume	29
Issue number	2
DOIs	https://doi.org/10.1063/1.5079686
Publication status	Published - 1 Feb 2019

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10.1063/1.5079686

Lymburn et al. 2019 Consistency in echo-state
This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Chaos 29, 023118 (2019) and may be found at https://aip.scitation.org/doi/abs/10.1063/1.5079686
Accepted author manuscript, 1.2 MBLicence: Other

Navigating tipping points in complex dynamical systems
Small, M. (Investigator 01), Lesterhuis, W. (Investigator 02), Bosco, A. (Investigator 03) & Zaitouny, A. (Investigator 04)
ARC Australian Research Council
1/01/18 → 31/12/21
Project: Research

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Consistency in echo-state networks

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Navigating tipping points in complex dynamical systems

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