Numerical Methods for General and Structured Eigenvalue Problems
The purpose of this book is to describe recent developments in solving eig- value problems, in particular with respect to the QR and QZ algorithms as well as structured matrices. Outline Mathematically speaking, the eigenvalues of a square matrix A are the roots of its characteristic polynomial det(...
שמור ב:
| מחבר ראשי: | |
|---|---|
| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Springer e-books
[20..].
Cham : Springer Nature |
| סדרה: | Lecture Notes in Computational Science and Engineering
46 |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
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| Edition sous un autre format: | • Numerical methods for general and structured eigenvalue problems, with 32 figures and 10 tables, Daniel Kressner, Berlin, Springer, 2005, 1 vol. (XIV-258 p.), Lecture notes in computational science and engineering, 3-540-24546-4 |
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| 245 | 1 | 0 | |a Numerical Methods for General and Structured Eigenvalue Problems |c by Daniel Kressner. |
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| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
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| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a The QR Algorithm The QZ Algorithm The Krylov-Schur Algorithm Structured Eigenvalue Problems Background in Control Theory Structured Eigenvalue Problems Software | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a The purpose of this book is to describe recent developments in solving eig- value problems, in particular with respect to the QR and QZ algorithms as well as structured matrices. Outline Mathematically speaking, the eigenvalues of a square matrix A are the roots of its characteristic polynomial det(A??I). An invariant subspace is a linear subspace that stays invariant under the action of A. In realistic applications, it usually takes a long process of simpli?cations, linearizations and discreti- tions before one comes up with the problem of computing the eigenvalues of a matrix. In some cases, the eigenvalues have an intrinsic meaning, e.g., for the expected long-time behavior of a dynamical system; in others they are just meaningless intermediate values of a computational method. The same applies to invariant subspaces, which for example can describe sets of initial states for which a dynamical system produces exponentially decaying states. Computing eigenvalues has a long history, dating back to at least 1846 when Jacobi [172] wrote his famous paper on solving symmetric eigenvalue problems. Detailed historical accounts of this subject can be found in two papers by Golub and van der Vorst [140, 327] | ||
| 776 | 0 | |0 101306369 |t Numerical methods for general and structured eigenvalue problems |o with 32 figures and 10 tables |f Daniel Kressner |c Berlin |n Springer |d 2005 |p 1 vol. (XIV-258 p.) |s Lecture notes in computational science and engineering |z 3-540-24546-4 | |
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