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Viser: Approximation of Large-Scale Dynamical Systems
Approximation of Large-Scale Dynamical Systems
Athanasios C. Antoulas
(2005)
Sprog: Engelsk
Society for Industrial and Applied Mathematics
2.371,00 kr.
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Detaljer om varen
- Paperback: 504 sider
- Udgiver: Society for Industrial and Applied Mathematics (December 2005)
- ISBN: 9780898716580
Mathematical models are used to simulate, and sometimes control, the behavior of physical and artificial processes such as the weather and very large-scale integration (VLSI) circuits. The increasing need for accuracy has led to the development of highly complex models. However, in the presence of limited computational, accuracy, and storage capabilities, model reduction (system approximation) is often necessary.
Approximation of Large-Scale Dynamical Systems provides a comprehensive picture of model reduction, combining system theory with numerical linear algebra and computational considerations. It addresses the issue of model reduction and the resulting trade-offs between accuracy and complexity. Special attention is given to numerical aspects, simulation questions, and practical applications.
Approximation of Large-Scale Dynamical Systems provides a comprehensive picture of model reduction, combining system theory with numerical linear algebra and computational considerations. It addresses the issue of model reduction and the resulting trade-offs between accuracy and complexity. Special attention is given to numerical aspects, simulation questions, and practical applications.
List of Figures Foreword Preface How to Use this Book
Part I: Introduction.
Chapter 1: Introduction
Chapter 2: Motivating Examples
Part II: Preliminaries.
Chapter 3: Tools from Matrix Theory
Chapter 4: Linear Dynamical Systems:
Part 1
Chapter 5: Linear Dynamical Systems:
Part 2
Chapter 6: Sylvester and Lyapunov equations
Part III: SVD-based Approximation Methods.
Chapter 7: Balancing and balanced approximations
Chapter 8: Hankel-norm Approximation
Chapter 9: Special topics in SVD-based approximation methods
Part IV: Krylov-based Approximation Methods
Chapter 10: Eigenvalue Computations
Chapter 11: Model Reduction Using Krylov Methods
Part V: SVD-Krylov Methods and Case Studies.
Chapter 12: SVD-Krylov Methods
Chapter 13: Case Studies
Chapter 14: Epilogue
Chapter 15: Problems Bibliography Index.
Part I: Introduction.
Chapter 1: Introduction
Chapter 2: Motivating Examples
Part II: Preliminaries.
Chapter 3: Tools from Matrix Theory
Chapter 4: Linear Dynamical Systems:
Part 1
Chapter 5: Linear Dynamical Systems:
Part 2
Chapter 6: Sylvester and Lyapunov equations
Part III: SVD-based Approximation Methods.
Chapter 7: Balancing and balanced approximations
Chapter 8: Hankel-norm Approximation
Chapter 9: Special topics in SVD-based approximation methods
Part IV: Krylov-based Approximation Methods
Chapter 10: Eigenvalue Computations
Chapter 11: Model Reduction Using Krylov Methods
Part V: SVD-Krylov Methods and Case Studies.
Chapter 12: SVD-Krylov Methods
Chapter 13: Case Studies
Chapter 14: Epilogue
Chapter 15: Problems Bibliography Index.
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