Numerical Methods in Matrix Computations

Author:   Åke Björck
Publisher:   Springer International Publishing AG
Edition:   2015 ed.
Volume:   59
ISBN:  

9783319050881


Pages:   800
Publication Date:   20 October 2014
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Numerical Methods in Matrix Computations


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Overview

Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated methods is given. Numerical Methods in Matrix Computations is suitable for use in courses on scientific computing and applied technical areas at advanced undergraduate and graduate level. A large bibliography is provided, which includes both historical and review papers as well as recent research papers. This makes the book useful also as a reference and guide to further study and research work.

Full Product Details

Author:   Åke Björck
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2015 ed.
Volume:   59
Dimensions:   Width: 15.50cm , Height: 4.30cm , Length: 23.50cm
Weight:   1.513kg
ISBN:  

9783319050881


ISBN 10:   3319050885
Pages:   800
Publication Date:   20 October 2014
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

From the book reviews: This is a fundamental work giving the basic ideas and methods in modern computational linear algebra. ... many ideas are mentioned and many references are given. Therefore, it will be an excellent reference work, parts can be used to teach a course on the subject, or it can be used by an independent reader to get a grasp on the topic, i.e., to learn something of the background, not just a practical hands-on programming course. (Adhemar Bultheel, euro-math-soc.au, December, 2014)


NMMC contains, of course, all expected classical topics and results on matrix computations, but it also contains very recent material ... . this is a very well written excellent book, which I strongly recommend to anybody interested in matrix computations and in computational mathematics in general. ... should be very useful for a wide audience, ranging from graduate students to specialists in matrix computations, as well as researchers in other areas that use matrix computations. (Froilan M. Dopico, SIAM Review, Vol. 58 (2), June, 2016) This remarkable book aims at providing an up-to-date treatment of methods and algorithms within the context of matrix computations and really hits the target. ... the interested reader can find a large, comprehensive and up-to-date list of references at the end of each chapter, together with some critical notes. ... this book is to be highly recommended to anybody with a serious interest in using matrix computations. (Raffaella Pavani, Mathematical Reviews, March, 2016) This is a fundamental work giving the basic ideas and methods in modern computational linear algebra. ... many ideas are mentioned and many references are given. Therefore, it will be an excellent reference work, parts can be used to teach a course on the subject, or it can be used by an independent reader to get a grasp on the topic, i.e., to learn something of the background, not just a practical hands-on programming course. (Adhemar Bultheel, euro-math-soc.au, December, 2014)


Author Information

Åke Björck is professor emeritus at Linköping University Sweden. He is the coauthor of several textbooks on numerical methods and a monograph and several papers on least squares methods. He has been visiting professor at Stanford University and University of Southern California.

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