A package for the sparse identification of nonlinear dynamical systems from data
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Updated
Jun 19, 2024 - Python
A package for the sparse identification of nonlinear dynamical systems from data
A Python Package For System Identification Using NARMAX Models
Control adaptive filters with neural networks.
A framework for gene expression programming (an evolutionary algorithm) in Python
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
A fully-featured flight simulator, capable of real-time lifting-line aerodynamic modelling.
My collection of implementations of adaptive filters.
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
Continuous-time system identification with neural networks
System identification in PyTorch
Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dario Piga.
Codes accompanying the paper "Deep learning with transfer functions: new applications in system identification"
SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
An optimized LMS algorithm
System identification toolkit for multistep prediction using deep learning and hybrid methods.
Unscented estimation and adaptive control package
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