| Item Type |
Journal paper
|
| 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. |
| Authors |
Grigoryeva, Lyudmila & Ortega, Juan-Pablo |
| Journal or Publication Title |
Neural Networks |
| Language |
English |
| Subjects |
computer science |
| HSG Classification |
contribution to scientific community |
| HSG Profile Area |
SEPS - Quantitative Economic Methods |
| Refereed |
Yes |
| Date |
2018 |
| Volume |
108 |
| Page Range |
495-508 |
| Depositing User |
Prof. Ph.D Juan-Pablo Ortega Lahuerta
|
| Date Deposited |
10 Nov 2019 09:53 |
| Last Modified |
20 Jul 2022 17:40 |
| URI: |
https://www.alexandria.unisg.ch/publications/258283 |
Echo state networks are universal
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