Core-Chasing Algorithms for the Eigenvalue Problem Paperback / softback
by Jared L. Aurentz, Thomas Mach, Leonardo Robol, Raf Vandebril, David S. Watkins
Part of the Fundamentals of Algorithms series
Paperback / softback
Description
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.
While Francis's 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.
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:148 pages
- Publisher:Society for Industrial & Applied Mathematics,U.S.
- Publication Date:30/07/2018
- Category:
- ISBN:9781611975338
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:148 pages
- Publisher:Society for Industrial & Applied Mathematics,U.S.
- Publication Date:30/07/2018
- Category:
- ISBN:9781611975338
