UID:
edocfu_9960045441202883
Umfang:
1 online resource (X, 378 p.)
ISBN:
3-11-049896-0
Serie:
Model Order Reduction ; Volume 1
Inhalt:
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.
Anmerkung:
Description based upon print version of record.
,
Frontmatter --
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Preface to the first volume of Model Order Reduction --
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Contents --
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1 Model order reduction: basic concepts and notation --
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2 Balancing-related model reduction methods --
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3 Model order reduction based on moment-matching --
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4 Modal methods for reduced order modeling --
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5 Post-processing methods for passivity enforcement --
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6 The Loewner framework for system identification and reduction --
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7 Manifold interpolation --
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8 Vector fitting --
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9 Kernel methods for surrogate modeling --
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10 Kriging: methods and applications --
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Index
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In English.
Weitere Ausg.:
ISBN 3-11-050043-4
Sprache:
Englisch
DOI:
10.1515/9783110498967
