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Iterative solution of large sparse s...

Hackbusch, Wolfgang.

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Iterative solution of large sparse systems of equations

Record Type:	Electronic resources : Monograph/item
Title/Author:	Iterative solution of large sparse systems of equations/ by Wolfgang Hackbusch.
Author:	Hackbusch, Wolfgang.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xxiii, 509 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I: Linear Iterations -- Introduction -- Iterative Methods -- Classical Linear Iterations in the Positive Definite Case -- Analysis of Classical Iterations Under Special Structural Conditions -- Algebra of Linear Iterations -- Analysis of Positive Definite Iterations -- Generation of Iterations. Part II: Semi-Iterations and Krylov Methods -- Semi-Iterative Methods -- Gradient Methods -- Conjugate Gradient Methods and Generalizations -- Part III: Special Iterations -- Multigrid Iterations -- Domain Decomposition and Subspace Methods -- H-LU Iteration -- Tensor-based Methods -- Appendices.
Contained By:	Springer eBooks
Subject:	Iterative methods (Mathematics) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-28483-5
ISBN:	9783319284835

Iterative solution of large sparse systems of equations
Hackbusch, Wolfgang.

Iterative solution of large sparse systems of equations[electronic resource] /by Wolfgang Hackbusch. - 2nd ed. - Cham :Springer International Publishing :2016. - xxiii, 509 p. :ill., digital ;24 cm. - Applied mathematical sciences,v.950066-5452 ;. - Applied mathematical sciences ;v.176..

Part I: Linear Iterations -- Introduction -- Iterative Methods -- Classical Linear Iterations in the Positive Definite Case -- Analysis of Classical Iterations Under Special Structural Conditions -- Algebra of Linear Iterations -- Analysis of Positive Definite Iterations -- Generation of Iterations. Part II: Semi-Iterations and Krylov Methods -- Semi-Iterative Methods -- Gradient Methods -- Conjugate Gradient Methods and Generalizations -- Part III: Special Iterations -- Multigrid Iterations -- Domain Decomposition and Subspace Methods -- H-LU Iteration -- Tensor-based Methods -- Appendices.

In the second edition of this classic monograph, complete with four new chapters and updated references, readers will now have access to content describing and analysing classical and modern methods with emphasis on the algebraic structure of linear iteration, which is usually ignored in other literature. The necessary amount of work increases dramatically with the size of systems, so one has to search for algorithms that most efficiently and accurately solve systems of, e.g., several million equations. The choice of algorithms depends on the special properties the matrices in practice have. An important class of large systems arises from the discretization of partial differential equations. In this case, the matrices are sparse (i.e., they contain mostly zeroes) and well-suited to iterative algorithms. The first edition of this book grew out of a series of lectures given by the author at the Christian-Albrecht University of Kiel to students of mathematics. The second edition includes quite novel approaches.

ISBN: 9783319284835

Standard No.: 10.1007/978-3-319-28483-5doiSubjects--Topical Terms:

648278
Iterative methods (Mathematics)

LC Class. No.: QA297.8

Dewey Class. No.: 518.26

Iterative solution of large sparse systems of equations
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245 1 0 $a Iterative solution of large sparse systems of equations $h [electronic resource] / $c by Wolfgang Hackbusch.
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505 0 $a Part I: Linear Iterations -- Introduction -- Iterative Methods -- Classical Linear Iterations in the Positive Definite Case -- Analysis of Classical Iterations Under Special Structural Conditions -- Algebra of Linear Iterations -- Analysis of Positive Definite Iterations -- Generation of Iterations. Part II: Semi-Iterations and Krylov Methods -- Semi-Iterative Methods -- Gradient Methods -- Conjugate Gradient Methods and Generalizations -- Part III: Special Iterations -- Multigrid Iterations -- Domain Decomposition and Subspace Methods -- H-LU Iteration -- Tensor-based Methods -- Appendices.
520 $a In the second edition of this classic monograph, complete with four new chapters and updated references, readers will now have access to content describing and analysing classical and modern methods with emphasis on the algebraic structure of linear iteration, which is usually ignored in other literature. The necessary amount of work increases dramatically with the size of systems, so one has to search for algorithms that most efficiently and accurately solve systems of, e.g., several million equations. The choice of algorithms depends on the special properties the matrices in practice have. An important class of large systems arises from the discretization of partial differential equations. In this case, the matrices are sparse (i.e., they contain mostly zeroes) and well-suited to iterative algorithms. The first edition of this book grew out of a series of lectures given by the author at the Christian-Albrecht University of Kiel to students of mathematics. The second edition includes quite novel approaches.
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