Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint Boundary Value Problems
Title | Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint Boundary Value Problems PDF eBook |
Author | ENGELI |
Publisher | Birkhäuser |
Pages | 107 |
Release | 2012-12-06 |
Genre | Science |
ISBN | 3034872240 |
Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint Boundary Value Problems
Title | Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint Boundary Value Problems PDF eBook |
Author | M. Engeli |
Publisher | Birkhauser |
Pages | 108 |
Release | 1980-01-01 |
Genre | |
ISBN | 9780817600983 |
Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-adjoint Boundary Value Problems. By M. Engeli [and Others], Etc
Title | Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-adjoint Boundary Value Problems. By M. Engeli [and Others], Etc PDF eBook |
Author | METHODS. |
Publisher | |
Pages | 107 |
Release | 1959 |
Genre | |
ISBN |
Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint-Boundary Value Problems
Title | Refined Iterative Methods for Computation of the Solution and the Eigenvalues of Self-Adjoint-Boundary Value Problems PDF eBook |
Author | 3Island Press |
Publisher | |
Pages | 112 |
Release | 1959-01-01 |
Genre | |
ISBN | 9783034872256 |
Refined iterative methods for computation of the solution and the eigenvalues of selfadjoint boundary value problems, by M. Engeli
Title | Refined iterative methods for computation of the solution and the eigenvalues of selfadjoint boundary value problems, by M. Engeli PDF eBook |
Author | |
Publisher | |
Pages | |
Release | |
Genre | Boundary value problems |
ISBN |
Advances on Computer Mathematics and Its Applications
Title | Advances on Computer Mathematics and Its Applications PDF eBook |
Author | Elias A. Lipitakis |
Publisher | World Scientific |
Pages | 388 |
Release | 1993 |
Genre | Computers |
ISBN | 9789810212926 |
This volume contains selected papers of the proceedings of the first Hellenic Conference on Mathematics and Informatics (HERMIS '92). The main theme for HERMIS '92 Conference was Computer Mathematics, with special emphasis on Computational Mathematics, Operational Research and Statistics, and Mathematics in Economic Science. The presented papers of the HERMIS Conference have been classified into the following technical sessions: Numerical solution of Differential Equations, Parallel Processing and Parallel Algorithms, Optimization and Approximation, Algorithms in Operational Research and Control Theory, Statistical Methods and Analysis, Mathematics in Economic Science, Artificial Intelligence and Data Bases Technology.In addition, a number of selected research articles published recently in the Hellenic Mathematical Society Bulletin in the form of special issues on Computer Mathematics (Volumes 31 and 32) are also included.
Lanczos Algorithms for Large Symmetric Eigenvalue Computations
Title | Lanczos Algorithms for Large Symmetric Eigenvalue Computations PDF eBook |
Author | Jane K. Cullum |
Publisher | SIAM |
Pages | 290 |
Release | 2002-09-01 |
Genre | Mathematics |
ISBN | 0898715237 |
First published in 1985, this book presents background material, descriptions, and supporting theory relating to practical numerical algorithms for the solution of huge eigenvalue problems. This book deals with 'symmetric' problems. However, in this book, 'symmetric' also encompasses numerical procedures for computing singular values and vectors of real rectangular matrices and numerical procedures for computing eigenelements of nondefective complex symmetric matrices. Although preserving orthogonality has been the golden rule in linear algebra, most of the algorithms in this book conform to that rule only locally, resulting in markedly reduced memory requirements. Additionally, most of the algorithms discussed separate the eigenvalue (singular value) computations from the corresponding eigenvector (singular vector) computations. This separation prevents losses in accuracy that can occur in methods which, in order to be able to compute further into the spectrum, use successive implicit deflation by computed eigenvector or singular vector approximations.