dynamicslab/databook_matlab

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dynamicslab/databook_matlab

dynamicslab

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Matlab files with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz http://www.databookuw.com/

Data_Driven_Science_MATLAB_Demos

MATLAB demo code intended as a companion to the book:

Data Driven Science & Engineering: Machine Learning, Dynamical Systems, and Control
by S. L. Brunton and J. N. Kutz
Cambridge Textbook, 2019
Copyright 2019, All Rights Reserved
http://databookuw.com/

Please cite this book when using this code/data.

MATLAB code library by S. L. Brunton and J. N. Kutz.

This code makes use of data files not packaged in the repository. These may be downloaded here: http://databookuw.com/DATA.zip (unzip into same directory)

Python versions of these demos are available at https://github.com/dynamicslab/databook_python

Links to useful Github codes:

Chapter 1

— rSVD (N. Ben Erichson): https://github.com/erichson/rSVD

Chapter 3

— SSPOR (Krithika Manohar): https://github.com/kmanohar/SSPOR_pub

Chapter 7

— PDE-FIND (Sam Rudy): https://github.com/snagcliffs/PDE-FIND

— DeepKoopman (Bethany Lusch): https://github.com/BethanyL/DeepKoopman

— KRONIC (Eurika Kaiser): https://github.com/eurika-kaiser/KRONIC

Chapter 10

— SINDY-MPC (Eurika Kaiser): https://github.com/eurika-kaiser/SINDY-MPC

— MLC (Thomas Duriez, Bernd Noack): http://berndnoack.com/MachineLearningControl.php

Other codes that we found useful, but have not included in our repository because of copyright:

cvx: http://cvxr.com/cvx/download/

mp3readwrite: https://labrosa.ee.columbia.edu/matlab/mp3read.html

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

pykoopman

A package for computing data-driven approximations to the Koopman operator.

SINDy-PI

SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics

pysensors

PySensors is a Python package for sparse sensor placement

dominant-balance

Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)

Jupyter Notebook

hydrogym

An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.

Jupyter Notebook

modified-SINDy

Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data

Jupyter Notebook

langevin-regression

Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton

Jupyter Notebook

MultiArm-Pendulum

This repository is for our paper: "The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control." It contains all the CAD files we used to build the pendulum hardware, their corresponding user's manual, and data set we collected from our hardware, which is useful for Machine Learning and AI community.

deep-learning-fluids

A collection of codes and references for deep learning in fluid dynamics

Jupyter Notebook

ctf-dl-tutorial

CTF workshop deep learning tutorial and hackathon

Jupyter Notebook

Saddle-Mediated-Transport-of-Double-Pendulum

NormalFormAE

KoopmanRL-NeurIPS