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dc.contributor.authorManguğlu, Murat
dc.contributor.authorMehrmann, Volker
dc.description.abstractWe propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of equations in which the coefficient matrix is symmetric and indefinite with relatively small number of negative eigenvalues. The proposed scheme consists of an outer Minimum Residual (MINRES) iteration, preconditioned by an inner Conjugate Gradient (CG) iteration in which CG can be further preconditioned. The robustness of the proposed scheme is illustrated by solving indefinite linear systems that arise in the solution of quadratic eigenvalue problems in the context of model reduction methods for finite element models of disk brakes as well as on other problems that arise in a variety of applications.en
dc.subject.ddc510 Mathematiken
dc.subject.othersymmetric indefinite systemsen
dc.subject.otherKrylov subspace methoden
dc.subject.othersparse linear systemsen
dc.subject.otherpreconditioned minimum residual methoden
dc.subject.otherpreconditioned conjugate gradient methoden
dc.titleA robust iterative scheme for symmetric indefinite systemsen
dc.typeResearch Paperen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
tub.series.issuenumber2018, 08en
tub.series.namePreprint-Reihe des Instituts für Mathematik, Technische Universität Berlinen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften » Inst. Mathematikde
tub.subject.msc200065F10 Iterative methods for linear systemsen
tub.subject.msc200065F15 Eigenvalues, eigenvectorsen
Appears in Collections:Technische Universität Berlin » Publications

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