3 papers
math.DS2021
Using Echo State Networks to Approximate Value Functions for Control
Allen G. Hart, Kevin R. Olding, A. M. G. Cox +2
An Echo State Network (ESN) is a type of single-layer recurrent neural network with randomly-chosen internal weights and a trainable output layer. We prove under mild conditions th…
cs.LG2020
Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems
Allen G Hart, James L Hook, Jonathan H P Dawes
Echo State Networks (ESNs) are a class of single-layer recurrent neural networks with randomly generated internal weights, and a single layer of tuneable outer weights, which are u…
nlin.CD2019
Embedding and Approximation Theorems for Echo State Networks
Allen G Hart, James L Hook, Jonathan H P Dawes
Echo State Networks (ESNs) are a class of single layer recurrent neural networks that have enjoyed recent attention. In this paper we prove that a suitable ESN, trained on a series…