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Data-Driven Science and Engineering
Buch von J. Nathan Kutz
Sprache: Englisch

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Beschreibung
Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling 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.
Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling 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.
Über den Autor
Steven L. Brunton is Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and a Data-Science Fellow at the eScience Institute. His research applies data science and machine learning for dynamical systems and control to fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He has co-authored two textbooks, received the Army and Air Force Young Investigator awards, and was awarded the University of Washington College of Education teaching award.
Inhaltsverzeichnis
Part I. Dimensionality Reduction and Transforms: 1. Singular value decomposition; 2. Fourier and wavelet transforms; 3. Sparsity and compressed sensing; Part II. Machine Learning and Data Analysis: 4. Regression and model selection; 5. Clustering and classification; 6. Neural networks and deep learning; Part III. Dynamics and Control: 7. Data-driven dynamical systems; 8. Linear control theory; 9. Balanced models for control; 10. Data-driven control; Part IV. Reduced-Order Models: 11. Reduced-order models (ROMs); 12. Interpolation for parametric ROMs.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Seiten: 496
Inhalt: Gebunden
ISBN-13: 9781108422093
ISBN-10: 1108422098
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Kutz, J. Nathan
Hersteller: Cambridge University Press
Maße: 260 x 183 x 31 mm
Von/Mit: J. Nathan Kutz
Erscheinungsdatum: 28.02.2019
Gewicht: 1,121 kg
preigu-id: 114087952
Über den Autor
Steven L. Brunton is Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and a Data-Science Fellow at the eScience Institute. His research applies data science and machine learning for dynamical systems and control to fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He has co-authored two textbooks, received the Army and Air Force Young Investigator awards, and was awarded the University of Washington College of Education teaching award.
Inhaltsverzeichnis
Part I. Dimensionality Reduction and Transforms: 1. Singular value decomposition; 2. Fourier and wavelet transforms; 3. Sparsity and compressed sensing; Part II. Machine Learning and Data Analysis: 4. Regression and model selection; 5. Clustering and classification; 6. Neural networks and deep learning; Part III. Dynamics and Control: 7. Data-driven dynamical systems; 8. Linear control theory; 9. Balanced models for control; 10. Data-driven control; Part IV. Reduced-Order Models: 11. Reduced-order models (ROMs); 12. Interpolation for parametric ROMs.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Seiten: 496
Inhalt: Gebunden
ISBN-13: 9781108422093
ISBN-10: 1108422098
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Kutz, J. Nathan
Hersteller: Cambridge University Press
Maße: 260 x 183 x 31 mm
Von/Mit: J. Nathan Kutz
Erscheinungsdatum: 28.02.2019
Gewicht: 1,121 kg
preigu-id: 114087952
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