Core-Chasing Algorithms for the Eigenvalue Problem (Paperback)
Language: English
Published by Society for Industrial & Applied Mathematics,U.S., New York, 2018
- Softcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Condition: New
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Paperback. Eigenvalue computations are ubiquitous in science and engineering. John Franciss implicitly shifted QR algorithm has been the method of choice for small to medium sized eigenvalue problems since its invention in 1959. This book presents a new view of this classical algorithm. While Franciss original procedure chases bulges, the new version chases core transformations, which allows the development of fast algorithms for eigenvalue problems with a variety of special structures. This also leads to a fast and backward stable algorithm for computing the roots of a polynomial by solving the companion matrix eigenvalue problem. The authors received a SIAM Outstanding Paper prize for this work.This book will be of interest to researchers in numerical linear algebra and their students. Eigenvalue computations are ubiquitous in science and engineering. John Francis's implicitly shifted QR algorithm has been the method of choice for small to medium sized eigenvalue problems since its invention in 1959. This book presents a new view of this classical algorithm. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9781611975338
- Title
- Core-Chasing Algorithms for the Eigenvalue Problem (Paperback)
- Author
- Jared L. Aurentz
- Publisher
- Society for Industrial & Applied Mathematics,U.S., New York
- Publication year
- 2018
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1611975336
- ISBN 13
- 9781611975338
This book will be of interest to researchers in numerical linear algebra and their students.
"Synopsis" may belong to another edition of this title.
About the Author
Thomas Mach is an assistant professor at Nazarbayev University, Kazakhstan. He was one of the LAA Early Career Speakers at the 21st Conference of the International Linear Algebra Society in 2017. The author of more than 20 publications, his research interest is structure-preserving algorithms, especially for eigenvalue problems.
Leonardo Robol is a researcher at the Institute of Information Science and Technologies (ISTI) of the National Research Council in Italy (CNR). He was the recipient of the honorable mention for the Householder Prize award in 2017. His research interests include the use of rank structures in matrix computations, particularly eigenvalue problems and matrix equations.
Raf Vandebril is a professor at KU Leuven. His thesis led to two books on semiseparable matrices (eigenvalue problems and system solving) co-authored with Marc Van Barel and Nicola Mastronardi. His primary research interests are eigenvalue computations and structured matrices.
David S. Watkins is professor emeritus of mathematics at Washington State University. He is the author of three books on matrix computations and numerous scientific publications, including several articles in SIAM Review.
"About the title" may belong to another edition of this title.
Grand Eagle Retail
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