Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks
<|reference_start|>Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks: 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.<|reference_end|>
@article{sakaguchi2024machine,
    title={Machine Learning of Nonlinear Dynamical Systems with Control Parameters
  Using Feedforward Neural Networks},
    author={Hidetsugu Sakaguchi},
    journal={arXiv preprint arXiv:2409.07468},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.07468},
    primaryClass={nlin.CD cs.NE nlin.AO}
}