Higher Order Dynamic Mode Decomposition and Its Applications /
Higher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly ev...
| Päätekijät: | , , |
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| Aineistotyyppi: | software, multimedia |
| Kieli: | eng |
| Julkaistu: |
London : Academic Press,
2020
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| Aiheet: | |
| Linkit: | https://www.sciencedirect.com/book/9780128197431 |
| _version_ | 1826472300802736128 |
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| author | Vega, Jose Manuel, author 651104 Le Clainche, Soledad, author 651105 ScienceDirect (Online service) 7722 |
| author_facet | Vega, Jose Manuel, author 651104 Le Clainche, Soledad, author 651105 ScienceDirect (Online service) 7722 |
| author_sort | Vega, Jose Manuel, author 651104 |
| collection | OCEAN |
| description | Higher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly evolving field, which has applications in domains including engineering, medical, biological, and physical sciences, where it is providing ground-breaking insights into complex systems that exhibit rich multi-scale phenomena in both time and space. Starting with an introductory summary of established order reduction techniques like POD, DEIM, Koopman, and DMD, this book proceeds to provide a detailed explanation of higher order DMD, and to explain its advantages over other methods. Technical details of how the HODMD can be applied to a range of industrial problems will help the reader decide how to use the method in the most appropriate way, along with example MATLAB codes and advice on how to analyse and present results. |
| first_indexed | 2024-03-05T17:16:25Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:603936 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:16:25Z |
| publishDate | 2020 |
| publisher | London : Academic Press, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:6039362023-10-03T06:40:44ZHigher Order Dynamic Mode Decomposition and Its Applications / Vega, Jose Manuel, author 651104 Le Clainche, Soledad, author 651105 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 London : Academic Press,2020©2021engHigher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly evolving field, which has applications in domains including engineering, medical, biological, and physical sciences, where it is providing ground-breaking insights into complex systems that exhibit rich multi-scale phenomena in both time and space. Starting with an introductory summary of established order reduction techniques like POD, DEIM, Koopman, and DMD, this book proceeds to provide a detailed explanation of higher order DMD, and to explain its advantages over other methods. Technical details of how the HODMD can be applied to a range of industrial problems will help the reader decide how to use the method in the most appropriate way, along with example MATLAB codes and advice on how to analyse and present results.Includes index.1. General introduction and scope of the book -- 2. Higher order dynamic mode decomposition -- 3. HODMD applications to the analysis of flight tests and magnetic resonance -- 4. Spatio-temporal Koopman decomposition -- 5. Application of HODMD and STKD to some pattern forming systems -- 6. Applications of HODMD and STKD in fluid dynamics -- 7. Applications of HODMD and STKD in the wind industry -- 8. HODMD and STKD as data driven reduced order models -- 9. ConclusionsHigher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly evolving field, which has applications in domains including engineering, medical, biological, and physical sciences, where it is providing ground-breaking insights into complex systems that exhibit rich multi-scale phenomena in both time and space. Starting with an introductory summary of established order reduction techniques like POD, DEIM, Koopman, and DMD, this book proceeds to provide a detailed explanation of higher order DMD, and to explain its advantages over other methods. Technical details of how the HODMD can be applied to a range of industrial problems will help the reader decide how to use the method in the most appropriate way, along with example MATLAB codes and advice on how to analyse and present results.Decomposition methodDecomposition (Mathematics)Mathematical analysishttps://www.sciencedirect.com/book/9780128197431URN:ISBN:9780128197431Remote access restricted to users with a valid UTM ID via VPN. |
| spellingShingle | Decomposition method Decomposition (Mathematics) Mathematical analysis Vega, Jose Manuel, author 651104 Le Clainche, Soledad, author 651105 ScienceDirect (Online service) 7722 Higher Order Dynamic Mode Decomposition and Its Applications / |
| title | Higher Order Dynamic Mode Decomposition and Its Applications / |
| title_full | Higher Order Dynamic Mode Decomposition and Its Applications / |
| title_fullStr | Higher Order Dynamic Mode Decomposition and Its Applications / |
| title_full_unstemmed | Higher Order Dynamic Mode Decomposition and Its Applications / |
| title_short | Higher Order Dynamic Mode Decomposition and Its Applications / |
| title_sort | higher order dynamic mode decomposition and its applications |
| topic | Decomposition method Decomposition (Mathematics) Mathematical analysis |
| url | https://www.sciencedirect.com/book/9780128197431 |
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