Pregled bibliografske jedinice broj: 1196975
Numerical methods for accurate computation of the eigenvalues of Hermitian matrices and the singular values of general matrices
Numerical methods for accurate computation of the eigenvalues of Hermitian matrices and the singular values of general matrices // SeMA Journal. Boletin de la Sociedad Espanñola de Matemática Aplicada, 78 (2021), 1; 53-92 doi:10.1007/s40324-020-00229-8 (međunarodna recenzija, članak, znanstveni)
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Naslov
Numerical methods for accurate computation of the
eigenvalues of Hermitian matrices and the singular
values of general matrices
Autori
Drmač, Zlatko
Izvornik
SeMA Journal. Boletin de la Sociedad Espanñola de Matemática Aplicada (2254-3902) 78
(2021), 1;
53-92
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Backward error ; Condition number ; Eigenvalues ; Hermitian matrices ; Jacobi method ; LAPACK ; Perturbation theory ; Rank revealing decomposition ; Singular value decomposition
Sažetak
This paper offers a review of numerical methods for computation of the eigenvalues of Hermitian matrices and the singular values of general and some classes of structured matrices. The focus is on the main principles behind the methods that guarantee high accuracy even in the cases that are ill-conditioned for the conventional methods. First, it is shown that a particular structure of the errors in a finite precision implementation of an algorithm allows for a much better measure of sensitivity and that computation with high accuracy is possible despite a large classical condition number. Such structured errors incurred by finite precision computation are in some algorithms e.g. entry-wise or column-wise small, which is much better than the usually considered errors that are in general small only when measured in the Frobenius matrix norm. Specially tailored perturbation theory for such structured perturbations of Hermitian matrices guarantees much better bounds for the relative errors in the computed eigenvalues. Secondly, we review an unconventional approach to accurate computation of the singular values and eigenvalues of some notoriously ill-conditioned structured matrices, such as e.g. Cauchy, Vandermonde and Hankel matrices. The distinctive feature of accurate algorithms is using the intrinsic parameters that define such matrices to obtain a non-orthogonal factorization, such as the LDU factorization, and then computing the singular values of the product of thus computed factors. The state of the art software is discussed as well.
Izvorni jezik
Engleski
Znanstvena područja
Matematika
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-6268 - Stohastičke aproksimacije malog ranga i primjene na parametarski ovisne probleme (RandLRAP) (Grubišić, Luka, HRZZ - 2019-04) ( CroRIS)
HRZZ-IP-2013-11-9345 - Matematičko modeliranje, analiza i računanje s primjenama na kompleksne mehaničke sustave (MMACACMS) (Drmač, Zlatko, HRZZ - 2013-11) ( CroRIS)
Ustanove:
Prirodoslovno-matematički fakultet, Matematički odjel, Zagreb,
Prirodoslovno-matematički fakultet, Zagreb
Profili:
Zlatko Drmač
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus
Uključenost u ostale bibliografske baze podataka::
- MathSciNet
- Zentrallblatt für Mathematik/Mathematical Abstracts