AleksandarHaber / Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks

This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.

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Machine Learning of Dynamical Systems Using Recurrent Neural Networks

This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.

  • The file "system_identification_machine_learning.py" is the main file. You should start from here.
  • The file "backward euler.py" defines a function for discretizing the continuous-time system using the backward Euler method. It is called from the file "system_identification_machine_learning.py". The complete description of this project is given on my webpage: https://aleksandarhaber.github.io/

LICENSE: THIS CODE CAN BE USED FREE OF CHARGE ONLY FOR ACADEMIC AND EDUCATIONAL PURPOSES. THAT IS, IT CAN BE USED FREE OF CHARGE ONLY IF THE PURPOSE IS NON-COMMERCIAL AND IF THE PURPOSE IS NOT TO MAKE PROFIT OR EARN MONEY BY USING THIS CODE.

IF YOU WANT TO USE THIS CODE IN THE COMMERCIAL SETTING, THAT IS, IF YOU WORK FOR A COMPANY OR IF YOU ARE AN INDEPENDENT CONSULTANT AND IF YOU WANT TO USE THIS CODE, THEN WITHOUT MY PERMISSION AND WITHOUT PAYING THE PROPER FEE, YOU ARE NOT ALLOWED TO USE THIS CODE. YOU CAN CONTACT ME AT

aleksandar.haber@gmail.com

TO INFORM YOURSELF ABOUT THE LICENSE OPTIONS AND FEES FOR USING THIS CODE. ALSO, IT IS NOT ALLOWED TO (1) MODIFY THIS CODE IN ANY WAY WITHOUT MY PERMISSION. (2) INTEGRATE THIS CODE IN OTHER PROJECTS WITHOUT MY PERMISSION.

DELIBERATE OR INDELIBERATE VIOLATIONS OF THIS LICENSE WILL INDUCE LEGAL ACTIONS AND LAWSUITS.

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This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.

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