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Approximate greatest common divisors of several polynomials with linearly constrained coefficients and singular polynomials

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Published:09 July 2006Publication History

ABSTRACT

We consider the problem of computing minimal real or complex deformations to the coefficients in a list of relatively prime real or complex multivariate polynomials such that the deformed polynomials have a greatest common divisor (GCD) of at least a given degree k. In addition, we restrict the deformed coefficients by a given set of linear constraints, thus introducing the linearly constrained approximate GCD problem. We present an algorithm based on a version of the structured total least norm (STLN) method and demonstrate on a diverse set of benchmark polynomials that the algorithm in practice computes globally minimal approximations. As an application of the linearly constrained approximate GCD problem we present an STLN-based method that computes a real or complex polynomial the nearest real or complex polynomial that has a root of multiplicity at least k. We demonstrate that the algorithm in practice computes on the benchmark polynomials given in the literature the known globally optimal nearest singular polynomials. Our algorithms can handle, via randomized preconditioning, the difficult case when the nearest solution to a list of real input polynomials actually has non-real complex coefficients.

References

  1. Anda, A. A., and Park, H. Fast plane with dynamic scaling. SIAM J. Matrix Anal. Applic. 15 (1994), 162--174. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Anda, A. A., and Park, H. Self-scaling fast rotations for stiff and equality-constrained linear least squares problems. Linear Algebra and Applications 234 (1996), 137--161.Google ScholarGoogle ScholarCross RefCross Ref
  3. Beckermann, B., and Labahn, G. A fast and numerically stable Euclidean-like algorithm for detecting relative prime numerical polynomials. J. Symbolic Comput. 26 (1998), 691--714. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Botting, B., Giesbrecht, M., and May, J. Using Riemannian SVD for problems in approximate algebra. In Wang and Zhi {33}, pp. 209--219.Google ScholarGoogle Scholar
  5. Chu, M. T., Funderlic, R. E., and Plemmons, R. J. Structured low rank approximation. Linear Algebra and Applications 366 (2003), 157--172.Google ScholarGoogle ScholarCross RefCross Ref
  6. Corless, R. M., Gianni, P. M., Trager, B. M., and Watt, S. M. The singular value decomposition for polynomial systems. In Proc. 1995 Internat. Symp. Symbolic Algebraic Comput. ISSAC'95 (New York, N. Y., 1995), A. H. M. Levelt, Ed., ACM Press, pp. 96--103. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Corless, R. M., Watt, S. M., and Zhi, L. QR factoring to compute the GCD of univariate approximate polynomials. IEEE Transactions on Signal Processing 52 (Dec. 2004), 3394--3402. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Dunaway, D. K. Calculation of zeros of a real polynomial through factorization using Euclid's algorithm. SIAM J. Numer. Anal. 11, 6 (1974), 1087--1104.Google ScholarGoogle ScholarCross RefCross Ref
  9. Eckart, C., and Young, G. The approximation of one matrix by another of lower rank. Psychometrika 1, 3 (Sept. 1936), 211--218.Google ScholarGoogle ScholarCross RefCross Ref
  10. Gao, S., Kaltofen, E., May, J. P., Yang, Z., and Zhi, L. Approximate factorization of multivariate polynomials via differential equations. In Gutierrez {12}, pp. 167--174. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. von zur Gathen, J., and Gerhard, J. Modern Computer Algebra. Cambridge University Press, Cambridge, New York, Melbourne, 1999. Second edition 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Gutierrez, J., Ed. ISSAC 2004 Proc. 2004 Internat. Symp. Symbolic Algebraic Comput. (New York, N. Y., 2004), ACM Press.Google ScholarGoogle Scholar
  13. Hitz, M. A., and Kaltofen, E. Efficient algorithms for computing the nearest polynomial with constrained roots. In Proc. 1998 Internat. Symp. Symbolic Algebraic Comput. (ISSAC'98) (New York, N. Y., 1998), O. Gloor, Ed., ACM Press, pp. 236--243. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Kahan, W. Numerical linear algebra. Canadian Math. Bull. 9 (1966), 757--801.Google ScholarGoogle ScholarCross RefCross Ref
  15. Kaltofen, E., and May, J. On approximate irreducibility of polynomials in several variables. In ISSAC 2003 Proc. 2003 Internat. Symp. Symbolic Algebraic Comput. (New York, N. Y., 2003), J. R. Sendra, Ed., ACM Press, pp. 161--168. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Kaltofen, E., May, J., Yang, Z., and Zhi, L. Approximate factorization of multivariate polynomials using singular value decomposition. Manuscript, 22 pages. Submitted, Jan. 2006.Google ScholarGoogle Scholar
  17. Kaltofen, E., Yang, Z., and Zhi, L. Structured low rank approximation of a Sylvester matrix. Manuscript, 15 pages, Oct. 2005. Preliminary version in SNC 2005 Proceedings, Dongming Wang and Lihong Zhi eds., pp. 188--201, distributed at the International Workshop on Symbolic-Numeric Computation in Xi'an, China, July 19--21, 2005.Google ScholarGoogle Scholar
  18. Kaltofen, E., Yang, Z., and Zhi, L. Structured low rank approximation of a generalized Sylvester matrix. In Proc. of the Seventh Asian Symposium on Computer Mathematics (Seoul, South Korea, 2005), S. Pae and H. Park, Eds., Korea Institute for Advanced Study, pp. 219--222. Extended abstract.Google ScholarGoogle Scholar
  19. Kaltofen, E., Yang, Z., and Zhi, L. Approximate greatest common divisors of several polynomials with linearly constrained coefficients and singular polynomials. Manuscript, 16 pages, Apr. 2006.Google ScholarGoogle Scholar
  20. Karmarkar, N. K., and Lakshman Y. N. On approximate GCDs of univariate polynomials. J. Symbolic Comput. 26, 6 (1998), 653--666. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Lemmerling, P. Structured total least squares: analysis, algorithms and applications. Dissertation, Katholieke Universiteit Leuven, Belgium, 1999.Google ScholarGoogle Scholar
  22. Lemmerling, P., Mastronardi, N., and Van Huffel, S. Fast algorithm for solving the Hankel/Toeplitz Structured Total Least Squares problem. Numerical Algorithms 23 (2000), 371--392.Google ScholarGoogle ScholarCross RefCross Ref
  23. Li, B., Liu, Z., and Zhi, L. Fast low rank approximation of a Sylvester matrix. In Wang and Zhi {33}, pp. 202--208.Google ScholarGoogle Scholar
  24. Li, B., Yang, Z., and Zhi, L. Fast low rank approximation of a Sylvester matrix by structured total least norm. J. JSSAC (Japan Society for Symbolic and Algebraic Computation) 11, 3,4 (2005), 165--174.Google ScholarGoogle Scholar
  25. Mastronardi, N., Lemmerling, P., and Van Huffel, S. Fast structured total least squares algorithm for solving the basic deconvolution problem. SIAM J. Matrix Anal. Applic. 22, 2 (2000), 533--553. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. May, J. P. Approximate factorization of polynomials in many variables and other problems in approximate algebra via singular value decomposition methods. PhD thesis, North Carolina State Univ., Raleigh, North Carolina, Aug. 2005.Google ScholarGoogle Scholar
  27. Park, H., Zhang, L., and Rosen, J. B. Low rank approximation of a Hankel matrix by structured total least norm. BIT 39, 4 (1999), 757--779.Google ScholarGoogle ScholarCross RefCross Ref
  28. Pope, S., and Szanto, A. Nearest multivariate system with given root multiplicities. Manuscript available at http://www.math.ncsu.edu/~aszanto/papers.html, 2005.Google ScholarGoogle Scholar
  29. Rump, S. M. Structured perturbations part I: Normwise distances. SIAM J. Matrix Anal. Applic. 25, 1 (2003), 1--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Sasasaki, T., and Noda, M. T. Approximate square-free decomposition and root-finding of ill-conditioned algebraic equations. J. Inf. Process. 12 (1989), 159--168. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Schönhage, A. Quasi-gcd computations. Journal of Complexity 1 (1985), 118--137.Google ScholarGoogle ScholarCross RefCross Ref
  32. Stewart, G. W. Introduction to Matrix Computations. Academic Press, Inc., New York, 1973.Google ScholarGoogle Scholar
  33. Wang, D., and Zhi, L., Eds. Proc. 2005 International Workshop on Symbolic-Numeric (July 2005). Distributed at the Workshop in Xi'an, China.Google ScholarGoogle Scholar
  34. Zeng, Z., and Dayton, B. H. The approximate GCD of inexact polynomials part II: a multivariate algorithm. In Gutierrez {12}, pp. 320--327. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Zhi, L. Displacement structure in computing approximate GCD of univariate polynomials. In Proc. Sixth Asian Symposium on Computer Mathematics (ASCM 2003) (Singapore, 2003), Z. Li and W. Sit, Eds., vol. 10 of Lecture Notes Series on Computing, World Scientific, pp. 288--298.Google ScholarGoogle ScholarCross RefCross Ref
  36. Zhi, L., Noda, M.-T., Kai, H., and Wu, W. Hybrid method for computing the nearest singular polynomials. Japan J. Industrial and Applied Math. 21, 2 (June 2004), 149--162.Google ScholarGoogle ScholarCross RefCross Ref
  37. Zhi, L., and Wu, W. Nearest singular polynomial. J. Symbolic Comput. 26, 6 (1998), 667--675. Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          ISSAC '06: Proceedings of the 2006 international symposium on Symbolic and algebraic computation
          July 2006
          374 pages
          ISBN:1595932763
          DOI:10.1145/1145768
          • General Chair:
          • Barry Trager

          Copyright © 2006 ACM

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          Publication History

          • Published: 9 July 2006

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