Dynamic Mode Decomposition - J. Nathan Kutz, Steven L. Brunton, Bingni W. Brunton, Joshua L. Proctor

Dynamic Mode Decomposition

Data-Driven Modeling of Complex Systems
Buch | Softcover
248 Seiten
2017
Society for Industrial & Applied Mathematics,U.S. (Verlag)
978-1-61197-449-2 (ISBN)
94,75 inkl. MwSt
Data-driven dynamical systems is a burgeoning field connecting how measurements of nonlinear dynamical systems and/or complex systems are used with well-established methods in dynamical systems theory. This is the first book to address the DMD algorithm and present a pedagogical approach to all aspects of DMD currently or under development.
Data-driven dynamical systems is a burgeoning field, connecting how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is the first book to address the DMD algorithm and present a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development. By blending theoretical development, example codes, and applications, the theory and its many innovations and uses are showcased. The efficacy of the DMD algorithm is shown through the inclusion of example problems from engineering, physical sciences, and biological sciences, and the authors provide extensive MATLAB® code, data for intuitive examples of key methods, and graphical presentations. This book can therefore be used in courses that integrate data analysis with dynamical systems, and will be a useful resource for engineers and applied mathematicians.

J. Nathan Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics, Adjunct Professor of Physics and Electrical Engineering, and Senior Data Science Fellow with the eScience Institute at the University of Washington. Steven L. Brunton is an Assistant Professor of Mechanical Engineering, Adjunct Assistant Professor of Applied Mathematics, and a Data Science Fellow with the eScience Institute at the University of Washington. Bingni W. Brunton is the Washington Research Foundation Innovation Assistant Professor of Biology and a Data Science Fellow with the eScience Institute at the University of Washington. Joshua L. Proctor is an Associate Principal Investigator with the Institute for Disease Modeling, Washington, as well as Affiliate Assistant Professor of Applied Mathematics and Mechanical Engineering at the University of Washington.

Preface; Notation; Acronyms; 1. Dynamic mode decomposition: an introduction; 2. Fluid dynamics; 3. Koopman analysis; 4. Video processing; 5. Multiresolution DMD; 6. DMD with control; 7. Delay coordinates, ERA, and hidden Markov models; 8. Noise and power; 9. Sparsity and DMD; 10. DMD on nonlinear observables; 11. Epidemiology; 12. Neuroscience; 13. Financial trading; Glossary; Bibliography; Index.

Erscheinungsdatum
Zusatzinfo Worked examples or Exercises
Verlagsort New York
Sprache englisch
Maße 177 x 255 mm
Gewicht 550 g
Themenwelt Naturwissenschaften Physik / Astronomie Strömungsmechanik
ISBN-10 1-61197-449-6 / 1611974496
ISBN-13 978-1-61197-449-2 / 9781611974492
Zustand Neuware
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