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Deep Learning for Poincaré Maps by mike88malone88 is a document available to read on EtoBox.

What is Deep Learning for Poincaré Maps about?

This document presents a method for obtaining explicit Poincaré mappings of chaotic dynamical systems using deep learning to create invertible coordinate transformations. It leverages an autoencoder to classify chaotic systems through topological conjugacies, enabling improved forecasting, dimensionality reduction, and interpretable mappings. The approach is demonstrated on both low-dimensional systems like the Rössler and Lorenz systems, and infinite-dimensional systems such as the Kuramoto–Sivashinsky equ

Author

mike88malone88

Language

EN