Recursive approximation of the dominant eigenspace of an indefinite matrix (Articolo in rivista)

Type
Label
  • Recursive approximation of the dominant eigenspace of an indefinite matrix (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.cam.2012.02.032 (literal)
Alternative label
  • Mastronardi Nicola; Van Dooren Paul (2012)
    Recursive approximation of the dominant eigenspace of an indefinite matrix
    in Journal of computational and applied mathematics; Elsevier BV, Amsterdam (Paesi Bassi)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Mastronardi Nicola; Van Dooren Paul (literal)
Pagina inizio
  • 4090 (literal)
Pagina fine
  • 4104 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.sciencedirect.com/science/article/pii/S0377042712000994 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 236 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 15 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 16 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto per le Applicazioni del Calcolo ``M. Picone'', sede di Bari, Consiglio Nazionale delle Ricerche, Via G. Amendola, 122/D, I-70126 Bari, Italy. Department of Mathematical Engineering, Catholic University of Louvain, Batiment Euler, Avenue Georges Lemaitre 4, B-1348 Louvain-la-Neuve, Belgium. (literal)
Titolo
  • Recursive approximation of the dominant eigenspace of an indefinite matrix (literal)
Abstract
  • We consider here the problem of tracking the dominant eigenspace of an indefinite matrix by updating recursively a rank k approximation of the given matrix. The tracking uses a window of the given matrix, which increases at every step of the algorithm. Therefore, the rank of the approximation increases also, and hence a rank reduction of the approximation is needed to retrieve an approximation of rank k. In order to perform the window adaptation and the rank reduction in an efficient manner, we make use of a new antitriangular decomposition for indefinite matrices. All steps of the algorithm only make use of orthogonal transformations, which guarantees the stability of the intermediate steps. We also show some numerical experiments to illustrate the performance of the tracking algorithm. (literal)
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