The Formulation and Analysis of Numerical Methods for Inverse Eigenvalue
Language: English
Published by Forgotten Books, 2018
- Softcover
- New
Seller: Forgotten Books, London, United KingdomForgotten Books
AbeBooks seller since June 2, 2021
Condition: New
US$ 17.72
Quantity: Over 20 available
Add to basketItem description from seller
Print on Demand. This insightful book advances our understanding of inverse eigenvalue problems in the field of computational science, exploring analytically how to solve the equations that underpin them. It considers the case where multiple eigenvalues are given and offers a practical methodology for obtaining quadratically convergent solutions for both distinct and multiple eigenvalue cases. The methods are illustrated with numerical experiments, elucidating their application. This book provides a comprehensive guide to solving inverse eigenvalue problems, describing not only how to find solutions but also the limits of convergence. It is essential reading for researchers and practitioners working on the theoretical and practical aspects of inverse eigenvalue problems. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.…
Seller Inventory # 9781332974085_0
- Title
- The Formulation and Analysis of Numerical Methods for Inverse Eigenvalue
- Author
- S. Friedland, J. Nocedal
- Publisher
- Forgotten Books
- Publication year
- 2018
- Condition
- New
- Book Type
- print-on-demand item
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1332974082
- ISBN 13
- 9781332974085
- Seller catalogs
- Calculus
The text introduces the core problems, such as adding or scaling parts of a matrix to force it to have specified eigenvalues, and it explains how to adapt methods for various variations found in engineering and science. Readers will see Newton-type strategies, inverse-iteration techniques, and modifications that maintain fast convergence even in challenging cases with multiple eigenvalues. Concrete examples and detailed discussions of convergence help bridge theory and practice.
- Learn the key problem formulations and when classical methods need adjustments
- See how to handle distinct versus multiple eigenvalues in a unified framework
- Understand how to modify approaches to achieve quadratic convergence
- Review numerical experiments that illustrate performance and limits
Ideal for readers of advanced undergraduate and graduate courses in numerical analysis, applied mathematics, and engineering who seek solid, implementation-ready insight into inverse eigenvalue computations.
"Synopsis" may belong to another edition of this title.
Forgotten Books
London, United Kingdom
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Forgotten Books’ Classic Reprint Series utilizes the latest technology to regenerate facsimiles of historically important writings. Careful attention has been made to accurately preserve the original format of each page whilst digitally enhancing the quality of the aged text.
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