Description
As experimental data sets have grown and computational power has increased, new tools have been developed that have the power to model new systems and fundamentally alter how current systems are analyzed. This book brings together modern computational tools to provide an accurate understanding of dynamic data. The techniques build on pencil-and-paper mathematical techniques that go back decades and sometimes even centuries. The result is an introduction to state-of-the-art methods that complement, rather than replace, traditional analysis of time-dependent systems.
Data-Driven Methods for Dynamic Systems provides readers with methods not found in other texts as well as novel ones developed just for this book; an example-driven presentation that provides background material and descriptions of methods without getting bogged down in technicalities; and examples that demonstrate the applicability of a method and introduce the features and drawbacks of their application. The online supplementary material includes a code repository that can be used to reproduce every example and that can be repurposed to fit a variety of applications not found in the book.
This book is intended as an introduction to the field of data-driven methods for graduate students. It will also be of interest to researchers who want to familiarize themselves with the discipline. It can be used in courses on dynamical systems, differential equations, and data science.
About the Author
Jason Bramburger is an assistant professor of mathematics at Concordia University. Previously, he was an NSERC postdoctoral fellow at Brown University, a PIMS postdoctoral fellow at the University of Victoria, and a member of the Brunton-Kutz research group at the University of Washington. In 2021 he was named a fellow of the Institute of Advanced Study in Guildford, UK. His mathematical expertise is in dynamical systems, which he applies broadly to problems in pattern formation, wave propagation, spatiotemporal chaos, and data science. Jason has a passion for outreach and effective communication, as demonstrated by expository articles and an active YouTube channel with course lectures on differential equations, mathematical modeling, and dynamical systems.
Book Information
ISBN 9781611978155
Author Jason J. Bramburger
Format Paperback
Page Count 169
Imprint Society for Industrial & Applied Mathematics,U.S.
Publisher Society for Industrial & Applied Mathematics,U.S.
Data-Driven Methods for Dynamic Systems provides readers with methods not found in other texts as well as novel ones developed just for this book; an example-driven presentation that provides background material and descriptions of methods without getting bogged down in technicalities; and examples that demonstrate the applicability of a method and introduce the features and drawbacks of their application. The online supplementary material includes a code repository that can be used to reproduce every example and that can be repurposed to fit a variety of applications not found in the book.
This book is intended as an introduction to the field of data-driven methods for graduate students. It will also be of interest to researchers who want to familiarize themselves with the discipline. It can be used in courses on dynamical systems, differential equations, and data science.
About the Author
Jason Bramburger is an assistant professor of mathematics at Concordia University. Previously, he was an NSERC postdoctoral fellow at Brown University, a PIMS postdoctoral fellow at the University of Victoria, and a member of the Brunton-Kutz research group at the University of Washington. In 2021 he was named a fellow of the Institute of Advanced Study in Guildford, UK. His mathematical expertise is in dynamical systems, which he applies broadly to problems in pattern formation, wave propagation, spatiotemporal chaos, and data science. Jason has a passion for outreach and effective communication, as demonstrated by expository articles and an active YouTube channel with course lectures on differential equations, mathematical modeling, and dynamical systems.
Book Information
ISBN 9781611978155
Author Jason J. Bramburger
Format Paperback
Page Count 169
Imprint Society for Industrial & Applied Mathematics,U.S.
Publisher Society for Industrial & Applied Mathematics,U.S.
