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Echo state networks are universal
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DOI：10.1016/j.neunet.2018.08.025.png)
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Abstract
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This paper shows that echo state networks are universal uniform approximants in the context of discrete-time fading memory filters with uniformly bounded inputs defined on negative infinite times. This result guarantees that any fading memory input/output system in discrete time can be realized as a simple finite-dimensional neural network-type state-space model with a static linear readout map. This approximation is valid for infinite time intervals. The proof of this statement is based on fundamental results, also presented in this work, about the topological nature of the fading memory property and about reservoir computing systems generated by continuous reservoir maps. (c) 2018 Elsevier Ltd. All rights reserved.
Keywords:
Reservoir computing (RC)
Universality
Echo state networks (ESN)
Machine learning
Fading memory filters
Uniform system approximation
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