Verlagslink DOI: 10.1137/040616097
Titel: An a priori bound for Automated Multi-Level Substructuring
Sprache: Englisch
Autor/Autorin: Voß, Heinrich
Elssel, Kolja
Schlagwörter: Eigenvalues;AMLS;substructuring;nonlinear eigenproblem;minmax characterization
Erscheinungsdatum: 2004
Quellenangabe: Preprint. Published in: SIAM. J. Matrix Anal. & Appl., 28.2006,2, 386–397
Serie/Report Nr.: Preprints des Institutes für Mathematik;Bericht 81
Zusammenfassung (deutsch): The Automated Multi-Level Substructuring (AMLS) method has been developed to reduce the computational demands of frequency response analysis and has recently been proposed as an alternative to iterative projection methods like Lanczos or Jacobi–Davidson for computing a large number of eigenvalues for matrices of very large dimension. Based on Schur complements and modal approximations of submatrices on several levels AMLS constructs a projected eigenproblem which yields good approximations of eigenvalues at the lower end of the spectrum. Rewriting the original problem as a rational eigenproblem of the same dimension as the projected problem, and taking advantage of a minmax characterization for the rational eigenproblem we derive an a priori bound for the AMLS approximation of eigenvalues.
URI: http://tubdok.tub.tuhh.de/handle/11420/65
URN: urn:nbn:de:gbv:830-opus-1186
DOI: 10.15480/882.63
Institut: Mathematik E-10
Mathematics E-10
Dokumenttyp: Preprint (Vorabdruck)
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