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| Auteur principal: | |
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| Format: | Recurso digital |
| Langue: | anglais |
| Publié: |
Zenodo
2025
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.5281/zenodo.14873595 |
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Table des matières:
- <p>Repository containing the code to reproduce the experiments in the paper "Input-Driven Dynamics for Robust Memory<br>Retrieval in Hopfield Networks". The code is commented to help the reader comprehend how the experiments unravels.</p> <p> The files are</p> <ul> <li>MainHNN_SHB.py Initializes the network, creates the input and calls the necessary classes to integrate the trajectories of the system</li> <li>HNN_Gen.py Class for the generation of the IDP Hopfield model (or the classic Hopfield model)</li> <li>Eul_May.py Class containing all the necessary function to implement the Euler-Maruyama method for the integration of SDE</li> <li>HNPlot.py Contains the functions necessary for the plotting of the trajectories</li> </ul>