Coder Social home page Coder Social logo

dynamicslab / databook_matlab Goto Github PK

View Code? Open in Web Editor NEW
245.0 10.0 96.0 3.71 MB

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/

MATLAB 94.75% M 0.06% C 5.19%

databook_matlab's Introduction

Data_Driven_Science_MATLAB_Demos

Data Driven Book Cover

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

databook_matlab's People

Contributors

dylewsky avatar eigensteve avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

databook_matlab's Issues

Full row/column rank matrices

Hi,
I couldn't find any other way to communicate with the authors of the book. Please excuse me for using this way.
Also I couldn't find an errata for the book, which i think it would be great to have in the website of the book.
My observation here is that the use of full column rank in the book, pp. 16 are not correct. A shirt-fat matrix cannot have full column rank by definition. Since rank(A) <= min(n,m) and in this case n<<m, the rank is at most n, which is the row rank. So a short-fat matrix is likely to have full row rank, not full column rank (number of linearly independent columns equals number of columns), as stated in the book.
In the same page it is also said that a tall-skinny matrix cannot have full column rank, when indeed this is the likely scenario.
I suspect that the authors are using a non-conventional definition of full column rank that they forgot to define.
The conventional definition is intuitive and consistent: column rank == number of linearly independent columns, hence full column rank means all columns are linearly independent.

Regards

Missing function 'delsearch' in CH04

The file delsearch.m is missing in directory CH04 which is needed in CH04_SEC02_1_GradientDescent.m

function mindel=delsearch(del,x,y,dfx,dfy,X,Y,F) 
x0=x-del*dfx;
y0=y-del*dfy;
mindel=interp2(X,Y,F,x0,y0);

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.