The first book to address the DMD algorithm and present a pedagogical approach to aspects of DMD currently or under development.
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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.
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Da: BooksRun, Philadelphia, PA, U.S.A.
Paperback. Condizione: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Codice articolo 1611974496-11-1
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Da: Webster's Bookstore Cafe, Inc., State College, PA, U.S.A.
paperback. Condizione: Very Good. A clean and tight copy. Codice articolo mon0000152939
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Codice articolo 1adee13901a44fd76f7bc728136b0303
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
Paperback. Condizione: New. 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.Dynamic Mode Decomposition is the first book to address the DMD algorithm, it:Presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development.Blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses.Highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences.Provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations. Codice articolo LU-9781611974492
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condizione: New. 2017. Paperback. . . . . . Codice articolo V9781611974492
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo FW-9781611974492
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Codice articolo 372006657
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 250 pages. 10.00x7.00x0.60 inches. In Stock. Codice articolo __1611974496
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Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New. 2017. Paperback. . . . . . Books ship from the US and Ireland. Codice articolo V9781611974492
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26375120094
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