Algorithms for Large Scale Linear Algebraic Systems

. Ed(s): Althaus, Gabriel Winter; Spedicato, Emilio Goiuseppe

ISBN 10: 079234975X / ISBN 13: 9780792349754

Published by Kluwer Academic Publishers, 1998

About this Item

Proceedings of the NATO Advanced Study Institute on Algorithms for Large Scale Linear Algebraic Systems: State of the Art and Applications in Science and Engineering, Gran Canaria, Spain, June 23-July 6, 1996 Editor(s): Althaus, Gabriel Winter; Spedicato, Emilio Goiuseppe. Series: NATO Science Series C. Num Pages: 418 pages, biography. BIC Classification: PBF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 23. Weight in Grams: 769. . 1998. Hardback. . . . .

Seller Inventory # V9780792349754

Bibliographic Details

• Title: Algorithms for Large Scale Linear Algebraic Systems
• Publisher: Kluwer Academic Publishers
• Publication Date: 1998
• Language: English
• ISBN 10: 079234975X
• ISBN 13: 9780792349754
• Binding: Hardcover
• Condition: New

About this title

Synopsis

An overview of the most successful algorithms and techniques for solving large, sparse systems of equations and some algorithms and strategies for solving optimization problems. The most important topics dealt with concern iterative methods, especially Krylov methods, ordering techniques, and some iterative optimization tools.
The book is a compendium of theoretical and numerical methods for solving large algebraic systems, special emphasis being placed on convergence and numerical behaviour as affected by rounding errors, accuracy in computing solutions for ill-conditioned matrices, preconditioning effectiveness, ordering procedures, stability factors, hybrid procedures and stopping criteria. Recent advances in numerical matrix calculations are presented, especially methods to accelerate the solution of symmetric and unsymmetric linear systems. Convergence analysis of the multi-grid method using a posteriori error estimation in second order elliptic equations are presented. Some inverse problems are also included. Evolution based software is described, such as genetic algorithms and evolution strategies, relations and class hierarchising to improve the exploration of large search spaces and finding near-global optima. Recent developments in messy genetic algorithms are also described.
The tutorial nature of the book makes it suitable for mathematicians, computer scientists, engineers and postgraduates.