Learning High-Dimensional Chaos Based on an Echo State Network with Homotopy Transformation

Learning High-Dimensional Chaos Based on an Echo State Network with Homotopy Transformation

Learning high-dimensional chaos is a complex and challenging problem because of its initial value-sensitive dependence. Based on an echo state network (ESN), we introduce homotopy transformation in topological theory to learn high-dimensional chaos. On the premise of maintaining the basic topologica...

Full description

Saved in:
Bibliographic Details
Main Authors: Shikun Wang, Fengjie Geng, Yuting Li, Hongjie Liu
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Mathematics
Subjects:
echo state network
homotopy theory
activation function
chaotic systems
Online Access:https://www.mdpi.com/2227-7390/13/6/894
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2227-7390/13/6/894

Similar Items