Golub and Meurant have shown how to use the symmetric block Lanczos algorithm to compute block Gauss quadrature rules for the approximation of certain matrix functions. We describe new block quadrature rules that can be computed by the symmetric or nonsymmetric block Lanczos algorithms and yield higher accuracy than standard block Gauss rules after the same number of steps of the symmetric or nonsymmetric block Lanczos algorithms. The new rules are block generalizations of the generalized averaged Gauss rules introduced by Spalevi´c. Applications to network analysis are presented

New block quadrature rules for the approximation of matrix functions

RODRIGUEZ, GIUSEPPE;
2016-01-01

Abstract

Golub and Meurant have shown how to use the symmetric block Lanczos algorithm to compute block Gauss quadrature rules for the approximation of certain matrix functions. We describe new block quadrature rules that can be computed by the symmetric or nonsymmetric block Lanczos algorithms and yield higher accuracy than standard block Gauss rules after the same number of steps of the symmetric or nonsymmetric block Lanczos algorithms. The new rules are block generalizations of the generalized averaged Gauss rules introduced by Spalevi´c. Applications to network analysis are presented
matrix funcions; Gauss quadrature; block Lanczos algoritm; complex networks
File in questo prodotto:
File Dimensione Formato  
newbquad16.pdf

Solo gestori archivio

Tipologia: versione editoriale
Dimensione 616.01 kB
Formato Adobe PDF
616.01 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/113242
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 13
social impact