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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2507.09835 |
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| _version_ | 1866911053897531392 |
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| author | Carney, Meagan González-Tokman, Cecilia Kardkasem, Ruethaichanok Zhang, Hongkun |
| author_facet | Carney, Meagan González-Tokman, Cecilia Kardkasem, Ruethaichanok Zhang, Hongkun |
| contents | We introduce a method for learning chaotic maps using an improved autoencoder neural network that incorporates a conjugacy layer in the latent space. The added conjugacy layer transforms nonlinear maps into a simple piecewise linear map (the tent map) whilst enforcing dynamical principles of well-known and defective conjugacy functions that increase the accuracy and stability of the learned solution. We demonstrate the method's effectiveness on both continuous and piecewise chaotic one-dimensional maps and numerically illustrate improved performance over related traditional and recently emerged deep learning architectures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_09835 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Improved Autoencoder Conjugacy Network to Learn Chaotic Maps Carney, Meagan González-Tokman, Cecilia Kardkasem, Ruethaichanok Zhang, Hongkun Dynamical Systems We introduce a method for learning chaotic maps using an improved autoencoder neural network that incorporates a conjugacy layer in the latent space. The added conjugacy layer transforms nonlinear maps into a simple piecewise linear map (the tent map) whilst enforcing dynamical principles of well-known and defective conjugacy functions that increase the accuracy and stability of the learned solution. We demonstrate the method's effectiveness on both continuous and piecewise chaotic one-dimensional maps and numerically illustrate improved performance over related traditional and recently emerged deep learning architectures. |
| title | An Improved Autoencoder Conjugacy Network to Learn Chaotic Maps |
| topic | Dynamical Systems |
| url | https://arxiv.org/abs/2507.09835 |