Interpolatory Methods for Model Reduction
$178.91
- Paperback
232 pages
- Release Date
27 February 2020
Summary
Taming Complexity: Interpolatory Methods for Model Reduction
Dynamical systems are essential for modeling and predicting complex phenomena. As systems grow in size and complexity to meet demands for improved accuracy, direct simulation becomes computationally expensive. Model reduction addresses this challenge by replacing large systems of equations with fewer equations, carefully managing the potential loss of accuracy.
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Book Details
| ISBN-13: | 9781611976076 |
|---|---|
| ISBN-10: | 1611976073 |
| Series: | Computational Science and Engineering 21 |
| Author: | Athanasios C. Antoulas |
| Publisher: | Society for Industrial & Applied Mathematics,U.S. |
| Imprint: | Society for Industrial & Applied Mathematics,U.S. |
| Format: | Paperback |
| Number of Pages: | 232 |
| Release Date: | 27 February 2020 |
| Weight: | 530g |
| Dimensions: | 256mm x 179mm |
About The Author
Athanasios C. Antoulas
Athanasios C. Antoulas is a professor in the Department of Electrical and Computing Engineering at Rice University. He is a fellow of the Max-Planck Society, a fellow of the IEEE, and an adjunct professor of molecular and cellular biology at the Baylor College of Medicine.
Christopher Beattie is a professor in the Department of Mathematics and in the Division of Computational Modeling and Data Analytics at Virginia Tech.
Serkan Gugercin is the Class of 1950 Professor of Mathematics, deputy director of the Division of Computational Modeling and Data Analytics, and an affiliated faculty in the Department of Mechanical Engineering at Virginia Tech.
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