Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks
August 28, 2024 Β· Declared Dead Β· π Journal of the Physical Society of Japan
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Authors
Hidetsugu Sakaguchi
arXiv ID
2409.07468
Category
nlin.CD
Cross-listed
cs.NE,
nlin.AO
Citations
0
Venue
Journal of the Physical Society of Japan
Last Checked
3 months ago
Abstract
Several authors have reported that the echo state network reproduces bifurcation diagrams of some nonlinear differential equations using the data for a few control parameters. We demonstrate that a simpler feedforward neural network can also reproduce the bifurcation diagram of the logistics map and synchronization transition in globally coupled Stuart-Landau equations.
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