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An algorithm for the complete solution of quadratic eigenvalue problems

Published:03 May 2013Publication History
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Abstract

We develop a new algorithm for the computation of all the eigenvalues and optionally the right and left eigenvectors of dense quadratic matrix polynomials. It incorporates scaling of the problem parameters prior to the computation of eigenvalues, a choice of linearization with favorable conditioning and backward stability properties, and a preprocessing step that reveals and deflates the zero and infinite eigenvalues contributed by singular leading and trailing matrix coefficients. The algorithm is backward-stable for quadratics that are not too heavily damped. Numerical experiments show that our MATLAB implementation of the algorithm, quadeig, outperforms the MATLAB function polyeig in terms of both stability and efficiency.

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    • Published in

      cover image ACM Transactions on Mathematical Software
      ACM Transactions on Mathematical Software  Volume 39, Issue 3
      April 2013
      149 pages
      ISSN:0098-3500
      EISSN:1557-7295
      DOI:10.1145/2450153
      Issue’s Table of Contents

      Copyright © 2013 ACM

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      Publication History

      • Published: 3 May 2013
      • Accepted: 1 September 2012
      • Revised: 1 May 2012
      • Received: 1 December 2011
      Published in toms Volume 39, Issue 3

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