| Literature DB >> 30317134 |
Lyudmila Grigoryeva1, Juan-Pablo Ortega2.
Abstract
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.Keywords: Echo state networks (ESN); Fading memory filters; Machine learning; Reservoir computing (RC); Uniform system approximation; Universality
Mesh:
Year: 2018 PMID: 30317134 DOI: 10.1016/j.neunet.2018.08.025
Source DB: PubMed Journal: Neural Netw ISSN: 0893-6080