Using Hamiltonian Neural Networks to Model Two Coupled Duffing Oscillators
Authors
Gordei Pribõtkin, Stefania Tomasiello
Abstract
In this short note, the performance of two kinds of physics-guided computing schemes, namely the Hamiltonian Neural Network and the Port-Hamiltonian Neural Network, are discussed through the predicted dynamics of two coupled Duffing oscillators. First, we propose a new error bound which holds for both types of networks. Then, we numerically investigate some alternative activation functions in terms of prediction accuracy. The numerical results show the potential of the approaches when compared to the standard neural networks in the transient regime.
Keywords
Port-Hamiltonian Neural Network; Hamiltonian Neural Network; Forced system; Damped system
Citation
- Journal: Neural Processing Letters
- Year: 2023
- Volume: 55
- Issue: 6
- Pages: 8163–8180
- Publisher: Springer Science and Business Media LLC
- DOI: 10.1007/s11063-023-11306-0
BibTeX
@article{Prib_tkin_2023,
title={{Using Hamiltonian Neural Networks to Model Two Coupled Duffing Oscillators}},
volume={55},
ISSN={1573-773X},
DOI={10.1007/s11063-023-11306-0},
number={6},
journal={Neural Processing Letters},
publisher={Springer Science and Business Media LLC},
author={Pribõtkin, Gordei and Tomasiello, Stefania},
year={2023},
pages={8163--8180}
}
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