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dc.contributor.authorGillis, Nicolas
dc.contributor.authorMehrmann, Volker
dc.contributor.authorSharma, Punit
dc.description.abstractIn this paper, we study the nearest stable matrix pair problem: given a square matrix pair (E,A), minimize the Frobenius norm of (∆E,∆A) such that (E+\∆E,A+∆A) is a stable matrix pair. We propose a reformulation of the problem with a simpler feasible set byintroducing dissipative Hamiltonian (DH) matrix pairs: A matrix pair (E,A) is DH if A=(J-R)Q with skew-symmetric J, positive semidefinite R, and an invertible Q such that Q^TE is positive semidefinite. This reformulation has a convex feasible domain onto which it is easy to project. This allows us to employ a fast gradient method to obtain a nearby stable approximation of a given matrix pair.en
dc.subject.ddc510 Mathematiken
dc.subject.otherdissipative Hamiltonian systemen
dc.subject.otherdistance to stabilityen
dc.subject.otherconvex optimizationen
dc.titleComputing nearest stable matrix pairsen
dc.typeResearch Paperen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
tub.series.issuenumber2017, 04en
tub.series.namePreprint-Reihe des Instituts für Mathematik, Technische Universität Berlinen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften » Inst. Mathematikde
tub.subject.msc200093D09 Robust stabilityen
tub.subject.msc200065F15 Eigenvalues, eigenvectorsen
Appears in Collections:Technische Universität Berlin » Publications

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