Polynomial root computation by means of the LR algorithm
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Abstract
By representing the LR algorithm of Rutishauser and its variants in a polynomial setting, we derive numerical methods for approximating either all of the roots or a numberk of the roots of minimum modulus of a given polynomialp(t) of degreen. These methods share the convergence properties of the LR matrix iteration but, unlike it, they can be arranged to produce parallel and sequential algorithms which are highly efficient especially in the case wherek≪n.
AMS subject classification
65H05 65F15Key words
Root-finding algorithms LR matrix iterationPreview
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References
- 1.F. L. Bauer,Das Verfahren der Treppeniteration und verwandte verfahren zur Lösung algebraische Eigenwertprobleme, ZAMP VIII (1957), pp. 163–203.Google Scholar
- 2.D. Bini,Numerical computation of polynomial zeros by means of Aberth’s method, manuscript, 1994.Google Scholar
- 3.T. J. dekker and J. F. Traub,An analysis of the shifted LR algorithm, Numer. Math., 17 (1971), pp. 179–188.MATHMathSciNetCrossRefGoogle Scholar
- 4.T. J. Dekker and J. F. Traub,The shifted QR algorithm for Hermitian matrices, Linear Algebra Appl., 4 (1971), pp. 137–154.MATHMathSciNetCrossRefGoogle Scholar
- 5.L. Gemignani,Computing a factor of a polynomial by means of multishift LR algorithms, SIAM J. Matrix Anal. Appl., to appear.Google Scholar
- 6.W. W. Hager,Applied Numerical Linear Algebra, Prentice-Hall International Editions, Englewood Cliffs, NJ, 1988.MATHGoogle Scholar
- 7.M. A. Jenkins and J. F. Traub,A three-stage variable shift iteration for polynomial zeros and its relation to generalized Rayleigh iteration, Numer. Math., 14 (1970), pp. 256–263.MathSciNetCrossRefGoogle Scholar
- 8.M. A. Jenkins and J. F. Traub,A three-stage algorithm for real polynomials using quadratic iteration, SIAM J. Numer. Anal., 7 (1970), pp. 545–566.MATHMathSciNetCrossRefGoogle Scholar
- 9.M. A. Jenkins, J. F. Traub,Principles for testing polynomial zerofinding programs, Tech. Report, Department of Computer Science, Carnegie-Mellon University.Google Scholar
- 10.M. A. Jenkins, J. F. Traub,Program ZRPOLY International Mathematics and Statistics Library, Houston, Texas.Google Scholar
- 11.J. Kautsky and G. H. Golub,On the calculation of Jacobi matrices, Linear Algebra Appl., 52/53 (1983), pp. 439–455.MathSciNetGoogle Scholar
- 12.P. Henrici,Applied and Computational Analysis, Vol. 1, Wiley, New York, 1977.Google Scholar
- 13.A. S. Householder,The Numerical Treatment of a Single Nonlinear Equation, McGraw-Hill, 1970.Google Scholar
- 14.H. Rutishauser,Lectures on Numerical Mathematics, Birkhäuser, Boston, 1990.MATHGoogle Scholar
- 15.J. Sebastião e Silva,Sur une méthode d’approximation semblable a celle de Graeffe, Portugal. Math., 2 (1941), pp. 271–279.MATHGoogle Scholar
- 16.G. W. Stewart,On the companion operator for analytic functions, Numer. Math., 18 (1971), pp. 26–43.MATHMathSciNetCrossRefGoogle Scholar
- 17.K. C. Toh and L. N. Trefethen,Pseudozeros of polynomials and pseudospectra of companion matrices, Numer. Math., 68 (1994), pp. 403–425.MATHMathSciNetCrossRefGoogle Scholar
- 18.D. S. Watkins and L. Elsner,Convergence of algorithms of decomposition type for the eigenvalue problem, Linear Algebra Appl., 143 (1991), pp. 19–47.MATHMathSciNetCrossRefGoogle Scholar
- 19.J. H. Wilkinson,The Algebraic Eigenvalue Problem, Oxford U. P., 1965.Google Scholar
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