Model Order Reduction. Volume 1, System- and Data-Driven Methods and Algorithms / ed. by Peter Benner.
Material type: TextLanguage: English Series: Model Order Reduction ; Volume 1Publisher: Berlin ; Boston : De Gruyter, [2021]Copyright date: ©2021Description: 1 online resource (X, 378 p.)Content type:- text
- computer
- online resource
- 9783110498967
- 515.353
- Internet Access AEU
- Issued also in print.
Item type | Current library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|
E-Book | De Gruyter | Available |
Frontmatter -- 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
Open Access unrestricted online access star
https://purl.org/coar/access_right/c_abf2
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.
Issued also in print.
Mode of access: Internet via World Wide Web.
This eBook is made available Open Access under a CC BY-NC-ND 4.0 license:
https://creativecommons.org/licenses/by-nc-nd/4.0
https://www.degruyter.com/dg/page/open-access-policy
In English.
Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Dez 2022)
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