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Hierarchical matrices = algorithms a...

Hackbusch, Wolfgang.

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Hierarchical matrices = algorithms and analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Hierarchical matrices/ by Wolfgang Hackbusch.
Reminder of title:	algorithms and analysis /
Author:	Hackbusch, Wolfgang.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xxv, 511 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- Part I: Introductory and Preparatory Topics -- 1. Introduction -- 2. Rank-r Matrices -- 3. Introductory Example -- 4. Separable Expansions and Low-Rank Matrices -- 5. Matrix Partition -- Part II: H-Matrices and Their Arithmetic -- 6. Definition and Properties of Hierarchical Matrices -- 7. Formatted Matrix Operations for Hierarchical Matrices -- 8. H2-Matrices -- 9. Miscellaneous Supplements -- Part III: Applications -- 10. Applications to Discretised Integral Operators -- 11. Applications to Finite Element Matrices -- 12. Inversion with Partial Evaluation -- 13. Eigenvalue Problems -- 14. Matrix Functions -- 15. Matrix Equations -- 16. Tensor Spaces -- Part IV: Appendices -- A. Graphs and Trees -- B. Polynomials -- C. Linear Algebra and Functional Analysis -- D. Sinc Functions and Exponential Sums -- E. Asymptotically Smooth Functions -- References -- Index.
Contained By:	Springer eBooks
Subject:	Matrices. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-47324-5
ISBN:	9783662473245$q(electronic bk.)

Hierarchical matrices = algorithms and analysis /
Hackbusch, Wolfgang.

Hierarchical matricesalgorithms and analysis /[electronic resource] :by Wolfgang Hackbusch. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xxv, 511 p. :ill., digital ;24 cm. - Springer series in computational mathematics,v.490179-3632 ;. - Springer series in computational mathematics ;42..

Preface -- Part I: Introductory and Preparatory Topics -- 1. Introduction -- 2. Rank-r Matrices -- 3. Introductory Example -- 4. Separable Expansions and Low-Rank Matrices -- 5. Matrix Partition -- Part II: H-Matrices and Their Arithmetic -- 6. Definition and Properties of Hierarchical Matrices -- 7. Formatted Matrix Operations for Hierarchical Matrices -- 8. H2-Matrices -- 9. Miscellaneous Supplements -- Part III: Applications -- 10. Applications to Discretised Integral Operators -- 11. Applications to Finite Element Matrices -- 12. Inversion with Partial Evaluation -- 13. Eigenvalue Problems -- 14. Matrix Functions -- 15. Matrix Equations -- 16. Tensor Spaces -- Part IV: Appendices -- A. Graphs and Trees -- B. Polynomials -- C. Linear Algebra and Functional Analysis -- D. Sinc Functions and Exponential Sums -- E. Asymptotically Smooth Functions -- References -- Index.

This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.

ISBN: 9783662473245$q(electronic bk.)

Standard No.: 10.1007/978-3-662-47324-5doiSubjects--Topical Terms:

516894
Matrices.

LC Class. No.: QA188

Dewey Class. No.: 512.9434

Hierarchical matrices = algorithms and analysis /
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100 1 $a Hackbusch, Wolfgang. $3 1086630
245 1 0 $a Hierarchical matrices $h [electronic resource] : $b algorithms and analysis / $c by Wolfgang Hackbusch.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a xxv, 511 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer series in computational mathematics, $x 0179-3632 ; $v v.49
505 0 $a Preface -- Part I: Introductory and Preparatory Topics -- 1. Introduction -- 2. Rank-r Matrices -- 3. Introductory Example -- 4. Separable Expansions and Low-Rank Matrices -- 5. Matrix Partition -- Part II: H-Matrices and Their Arithmetic -- 6. Definition and Properties of Hierarchical Matrices -- 7. Formatted Matrix Operations for Hierarchical Matrices -- 8. H2-Matrices -- 9. Miscellaneous Supplements -- Part III: Applications -- 10. Applications to Discretised Integral Operators -- 11. Applications to Finite Element Matrices -- 12. Inversion with Partial Evaluation -- 13. Eigenvalue Problems -- 14. Matrix Functions -- 15. Matrix Equations -- 16. Tensor Spaces -- Part IV: Appendices -- A. Graphs and Trees -- B. Polynomials -- C. Linear Algebra and Functional Analysis -- D. Sinc Functions and Exponential Sums -- E. Asymptotically Smooth Functions -- References -- Index.
520 $a This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.
650 0 $a Matrices. $3 516894
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650 2 4 $a Numerical Analysis. $3 892626
650 2 4 $a Algorithms. $3 536374
650 2 4 $a Partial Differential Equations. $3 890899
650 2 4 $a Integral Equations. $3 897446
650 2 4 $a Linear and Multilinear Algebras, Matrix Theory. $3 891082
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer series in computational mathematics ; $v 42. $3 1568666
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-47324-5
950 $a Mathematics and Statistics (Springer-11649)