Trans-Bifurcation Prediction of Dynamics in terms of Extreme Learning Machines with Control Inputs
Chaotic Dynamics
2024-10-21 v1 Machine Learning
Machine Learning
Abstract
By extending the extreme learning machine by additional control inputs, we achieved almost complete reproduction of bifurcation structures of dynamical systems. The learning ability of the proposed neural network system is striking in that the entire structure of the bifurcations of a target one-parameter family of dynamical systems can be nearly reproduced by training on transient dynamics using only a few parameter values. Moreover, we propose a mechanism to explain this remarkable learning ability and discuss the relationship between the present results and similar results obtained by Kim et al.
Keywords
Cite
@article{arxiv.2410.13289,
title = {Trans-Bifurcation Prediction of Dynamics in terms of Extreme Learning Machines with Control Inputs},
author = {Satoru Tadokoro and Akihiro Yamaguchi and Takao Namiki and Ichiro Tsuda},
journal= {arXiv preprint arXiv:2410.13289},
year = {2024}
}