Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures-Reference-Cited by-同舟云学术

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Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures

Published:2023-04 Issue: Volume:446 Page:133656
ISSN:0167-2789
Container-title:Physica D: Nonlinear Phenomena
language:en
Short-container-title:Physica D: Nonlinear Phenomena

Author:

Zhong Ming,Yan Zhenya^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Reference57 articles.

1. The synchronization of chaotic systems;Boccaletti;Phys. Rep.,2002

2. From Chaos to Order: Methodologies, Perspectives and Applications;Chen,1998

3. Synchronization in chaotic systems;Pecora;Phys. Rev. Lett.,1990

4. Introduction to Applied Nonlinear Dynamical Systems and Chaos;Wiggins,2003

5. Differential Equations, Dynamical Systems, and an Introduction to Chaos;Hirsch,2012

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