Data-driven science and engineering : machine learning, dynamical systems, and control / Steven L. Brunton and J. Nathan Kutz.

By:

Brunton, Steven L. (Steven Lee), 1984- [author.]

Contributor(s):

Kutz, Jose Nathan [author.]

Material type: Text

TextPublisher: Cambridge, England : Cambridge University Press, 2019Description: xxii, 472 pages : illustrations ; 26 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781108422093

Subject(s):

DDC classification:

620.00285631 B838d 23

LOC classification:

TA330 .B78 2019

Contents:

Singular value decomposition (SVD) -- Fourier and wavelet transforms -- Sparsity and compressed sensing -- Regression and model selection -- Clustering and classification -- Neural networks and deep learning -- Data - driven dynamical systems -- Linear control theory -- Balanced models for control -- Data - driven control -- Reduced order models (ROMs) -- Interpolation for parametric ROMs.

Summary: "Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art"-- Provided by publisher.

Tags from this library: No tags from this library for this title. Log in to add tags.

Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	Main Library-Nabua	Graduate School Library	GRD 620.00285631 B838d 2019 (Browse shelf(Opens below))	1-1	Available		026269

Browsing Main Library-Nabua shelves, Shelving location: Graduate School Library Close shelf browser (Hides shelf browser)

Previous			No cover image available					Next
Previous	GRD 618.9289 C616 2020 Clinician's toolkit for children's behavioral health /	GRD 620.00151825 K560i 2018 Introduction to finite element analysis and design /	GRD 620.00285536 L811e 2019 An engineer's introduction to programming with MATLAB 2019 /	GRD 620.00285631 B838d 2019 Data-driven science and engineering : machine learning, dynamical systems, and control /	GRD 620.11 M418 2018 Materials science structure and characterization of materials	GRD 620.118 H991 2017 Hybrid nanomaterials design, synthesis, and biomedical applications/	GRD 620.8 D535e 2019 Environmental engineering and management	Next

Includes bibliographical references and index.

"Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art"-- Provided by publisher.

There are no comments on this title.

to post a comment.