Card | Table | RUSMARC | |
Model order reduction ;.
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Annotation
"An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques. "--.
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Finuniversity Local Network | All | |||||
Internet | Readers | |||||
Internet | Anonymous |
Table of Contents
- Preface to the first volume of Model Order Reduction
- Contents
- 1 Model order reduction: basic concepts and notation
- 2 Balancing-related model reduction methods
- 3 Model order reduction based on moment-matching
- 4 Modal methods for reduced order modeling
- 5 Post-processing methods for passivity enforcement
- 6 The Loewner framework for system identification and reduction
- 7 Manifold interpolation
- 8 Vector fitting
- 9 Kernel methods for surrogate modeling
- 10 Kriging: methods and applications
- Index
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