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

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Machine Learning of Dynamical Systems Using Recurrent Neural Networks

IMPORTANT NOTE: First, thoroughly read the license in the file called LICENSE.md!

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/

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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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