Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- A Note on the Notation
- Part I Motivation
- Part II Methods from Signal Processing
- Part III Data-Driven Decompositions
- 6 The Proper Orthogonal Decomposition
- 7 The Dynamic Mode Decomposition: From Koopman Theory to Applications
- 8 Generalized and Multiscale Modal Analysis
- 9 Good Practice and Applications of Data-Driven Modal Analysis
- Part IV Dynamical Systems
- Part V Applications
- Part VI Perspectives
- References
7 - The Dynamic Mode Decomposition: From Koopman Theory to Applications
from Part III - Data-Driven Decompositions
Published online by Cambridge University Press: 12 January 2023
- Frontmatter
- Contents
- Contributors
- Preface
- A Note on the Notation
- Part I Motivation
- Part II Methods from Signal Processing
- Part III Data-Driven Decompositions
- 6 The Proper Orthogonal Decomposition
- 7 The Dynamic Mode Decomposition: From Koopman Theory to Applications
- 8 Generalized and Multiscale Modal Analysis
- 9 Good Practice and Applications of Data-Driven Modal Analysis
- Part IV Dynamical Systems
- Part V Applications
- Part VI Perspectives
- References
Summary
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- Type
- Chapter
- Information
- Data-Driven Fluid MechanicsCombining First Principles and Machine Learning, pp. 133 - 152Publisher: Cambridge University PressPrint publication year: 2023