AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

Model-based Control using Koopman Operators

Koopman operator

a little library to help me with things involving Koopman operators

project for my essay on how to use neural networks to linearise nonlinear dynamical systems

In this work, we present a novel approach that combines the power of Koopman operators and deep neural networks to generate a linear representation of the Duffing oscillator. This approach enables effective parameter estimation and accurate prediction of the oscillator's future behavior.

This repository contains the code for bilinear models for serial manipulators and the corresponding ZNN controller developed for the purpose of trajectory tracking with the aforementioned models.

Library for the analysis of time-evolving graphs

Code for running the analyses from the article "Propofol destabilizies neural dynamics across cortex"

koopman operator examples

For research into the application of Koopman operators at Boston University.

Transfer operator toolbox for numpy/torch.

This repository is a supplementary documentation for the Multi-Model Parameterized Koopman (MMPK) framework capturing results through software and hardware deployments