Dynamic Mode Decomposition: Data-Driven Modeling of Complex...

Main
Mathematics - Applied Mathematics
Dynamic Mode Decomposition: Data-Driven...

Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems

Name: Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems
ISBN: 9781611974492

J. Nathan Kutz, Steven L. Brunton, Bingni W. Brunton, Joshua L. Proctor

5.0 / 5.0

0 comments

이 책이 얼마나 마음에 드셨습니까?

파일의 품질이 어떻습니까?

책의 품질을 평가하시려면 책을 다운로드하시기 바랍니다

다운로드된 파일들의 품질이 어떻습니까?

Data-driven dynamical systems is a burgeoning field—it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning.

카테고리:

Mathematics - Applied Mathematics

년:

2016

판:

출판사:

SIAM-Society for Industrial and Applied Mathematics

언어:

english

페이지:

241

ISBN 10: