Core-Chasing Algorithms for the Eigenvalue Problem (Paperback)

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.

General

Imprint:	Society For Industrial & Applied Mathematics,U.S.
Country of origin:	United States
Series:	Fundamentals of Algorithms
Release date:	July 2018
Authors:	Jared L. Aurentz • Thomas Mach • Leonardo Robol • Raf Vandebril • David S Watkins
Dimensions:	229 x 152 x 16mm (L x W x T)
Format:	Paperback
Pages:	148
ISBN-13:	978-1-61197-533-8
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Science & Mathematics > Mathematics > Applied mathematics > General Promotions
LSN:	1-61197-533-6
Barcode:	9781611975338

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