Literature DB >> 30317134

Echo state networks are universal.

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.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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


  6 in total

1.  Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere.

Authors:  Pietro Verzelli; Cesare Alippi; Lorenzo Livi
Journal:  Sci Rep       Date:  2019-09-25       Impact factor: 4.379

2.  An internet traffic classification method based on echo state network and improved salp swarm algorithm.

Authors:  Meijia Zhang; Wenwen Sun; Jie Tian; Xiyuan Zheng; Shaopeng Guan
Journal:  PeerJ Comput Sci       Date:  2022-02-28

3.  Neural kernels for recursive support vector regression as a model for episodic memory.

Authors:  Christian Leibold
Journal:  Biol Cybern       Date:  2022-03-29       Impact factor: 3.072

4.  Step-like dependence of memory function on pulse width in spintronics reservoir computing.

Authors:  Terufumi Yamaguchi; Nozomi Akashi; Kohei Nakajima; Hitoshi Kubota; Sumito Tsunegi; Tomohiro Taniguchi
Journal:  Sci Rep       Date:  2020-11-11       Impact factor: 4.379

5.  Towards Embedded Computation with Building Materials.

Authors:  Dawid Przyczyna; Maciej Suchecki; Andrew Adamatzky; Konrad Szaciłowski
Journal:  Materials (Basel)       Date:  2021-03-31       Impact factor: 3.623

6.  Probabilistic Deterministic Finite Automata and Recurrent Networks, Revisited.

Authors:  Sarah E Marzen; James P Crutchfield
Journal:  Entropy (Basel)       Date:  2022-01-06       Impact factor: 2.524

  6 in total

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