Controlling dynamical systems to complex target states using machine learning: next-generation vs. classical reservoir computing-Reference-Cited by-同舟云学术

Controlling dynamical systems to complex target states using machine learning: next-generation vs. classical reservoir computing

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
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Author:

Haluszczynski Alexander¹,Koeglmayr Daniel²,Räth Christoph²

Affiliation:

1. Allianz Global Investors,risklab,Munich,Germany

2. Institut für KI Sicherheit, Deutsches Zentrum für Luft- und Raumfahrt (DLR),Ulm,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191257.pdf?arnumber=10191257

Reference25 articles.

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2. Reservoir computing and its sensitivity to symmetry in the activation function;herteux;ArXiv Preprint,2020

3. Machine learning prediction of critical transition and system collapse

4. Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

5. Controlling nonlinear dynamical systems into arbitrary states using machine learning

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