Model Order Reduction: Theory, Research Aspects and Applications / edited by Wilhelmus H. A. Schilders, Henk A. Vorst, Joost Rommes.

Springer eBooks

Basic Concepts -- to Model Order Reduction -- Linear Systems, Eigenvalues, and Projection -- Theory -- Structure-Preserving Model Order Reduction of RCL Circuit Equations -- A Unified Krylov Projection Framework for Structure-Preserving Model Reduction -- Model Reduction via Proper Orthogonal Decomposition -- PMTBR: A Family of Approximate Principal-components-like Reduction Algorithms -- A Survey on Model Reduction of Coupled Systems -- Space Mapping and Defect Correction -- Modal Approximation and Computation of Dominant Poles -- Some Preconditioning Techniques for Saddle Point Problems -- Time Variant Balancing and Nonlinear Balanced Realizations -- Singular Value Analysis and Balanced Realizations for Nonlinear Systems -- Research Aspects and Applications -- Matrix Functions -- Model Reduction of Interconnected Systems -- Quadratic Inverse Eigenvalue Problem and Its Applications to Model Updating — An Overview -- Data-Driven Model Order Reduction Using Orthonormal Vector Fitting -- Model-Order Reduction of High-Speed Interconnects Using Integrated Congruence Transform -- Model Order Reduction for MEMS: Methodology and Computational Environment for Electro-Thermal Models -- Model Order Reduction of Large RC Circuits -- Reduced Order Models of On-Chip Passive Components and Interconnects, Workbench and Test Structures.

The goal of this book is three-fold: it describes the basics of model order reduction and related aspects. In numerical linear algebra, it covers both general and more specialized model order reduction techniques for linear and nonlinear systems, and it discusses the use of model order reduction techniques in a variety of practical applications. The book contains many recent advances in model order reduction, and presents several open problems for which techniques are still in development. It will serve as a source of inspiration for its readers, who will discover that model order reduction is a very exciting and lively field.

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