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Convergence Theory of Probability-one Homotopies for Model Order Reduction

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dc.contributor.authorWang, Chang Y.en
dc.contributor.authorBernstein, Dennis S.en
dc.contributor.authorWatson, Layne T.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:35:45Zen
dc.date.available2013-06-19T14:35:45Zen
dc.date.issued1996-06-01en
dc.description.abstractThe optimal H-square model reduction problem is an inherently nonconvex problem and thus provides a nontrivial computational challenge. This paper systematically examines the requirements of probability-one homotopy methods to guarantee global convergence. Homotopy algorithms for nonlinear systems of equations construct a continuous family of systems, and solve the given system by tracking the continuous curve of solutions to the family. The main emphasis is on guaranteeing transversality for several homotopy maps based upon the pseudogramian formulation of the optimal projection equations and variations based upon canonical forms. These results are essential to the probability-one homotopy approach by guaranteeing good numerical properties in the computation- al implementation of the homotopy algorithms.en
dc.format.mimetypeapplication/postscripten
dc.identifierhttp://eprints.cs.vt.edu/archive/00000449/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00000449/01/TR-96-10.psen
dc.identifier.trnumberTR-96-10en
dc.identifier.urihttp://hdl.handle.net/10919/19920en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofHistorical Collection(Till Dec 2001)en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleConvergence Theory of Probability-one Homotopies for Model Order Reductionen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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