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Solving toeplitz- and vandermonde-like linear systems with large displacement rank

Published:29 July 2007Publication History

ABSTRACT

Linear systems with structures such as Toeplitz-, Vandermonde-or Cauchy-likeness can be solved in O~(α2n) operations, where n is the matrix size, α is its displacement rank, and O~denotes the omission of logarithmic factors. We show that for Toeplitz-like and Vandermonde-like trices, this cost can be reduced to O~(αω--1 n), where ω is a feasible exponent for matrix multiplication over the base field. The best known estimate for ω is ω< 2.38, resulting in costs of order O~(α1.38n). We also present consequences for Hermite-Padé approximation and bivariate interpolation.

References

  1. B. Beckermann. A reliable method for computing M-Padé approximants on arbitrary staircases. J. Comput. Appl. Math., 40(1):19--42, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. B. Beckermann and G. Labahn. A uniform approach for the fast computation of matrix-type Padé approximants. SIAM J. Matrix Anal. Appl., 15(3):804--823, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. B. Beckermann and G. Labahn. Fraction-free computation of matrix rational interpolants and matrix GCDs. SIAM J. Matrix Anal. Appl., 22(1):114--144, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. Ben-Or and P. Tiwari. A deterministic algorithm for sparse multivariate polynomial interpolation. In 20th Annual ACM Symp. Theory Comp., pages 301--309, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Bini and V. Y. Pan. Polynomial and Matrix Computations, volume 1: Fundamental Algorithms.Birkhäuser, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. R. R. Bitmead and B. D. O. Anderson. Asymptotically fast solution of Toeplitz and related systems of linear equations. Linear Algebra Appl., 34:103--116, 1980.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. Bostan, C.-P. Jeannerod, and É. Schost. Solving structured linear systems with large displacement rank. Technical report.Google ScholarGoogle Scholar
  8. J. Canny, E. Kaltofen, and Y. Lakshman. Solving systems of non-linear polynomial equations faster. In ISSAC'89, pages 121--128. ACM, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. D. G. Cantor and E. Kaltofen. On fast multiplication of polynomials over arbitrary algebras. Acta Informatica, 28(7):693--701, 1991. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. D. Coppersmith and S. Winograd. Matrix multiplication via arithmetic progressions. J. Symb. Comput., 9(3):251--280, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. R. A. DeMillo and R. J. Lipton. A probabilistic remark on algebraic program testing. Inf. Process. Lett., 7(4):193--195, 1978.Google ScholarGoogle ScholarCross RefCross Ref
  12. J.-G. Dumas, T. Gautier, and C. Pernet. Finite field linear algebra subroutines. In ISSAC'02, pages 63--74. ACM, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. W. Eberly, M. Giesbrecht, P. Giorgi, A. Storjohann, and G. Villard. Solving sparse rational linear systems. In ISSAC'06, pages 63--70. ACM, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Gao, V. M. Rodrigues, and J. Stroomer. Gröbner basis structure of finite sets of points, preprint, 2003.Google ScholarGoogle Scholar
  15. M. Gasca and T. Sauer. Polynomial interpolation in several variables. Adv. Comput. Math., 12(4):377--410, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  16. J. von zur Gathen and J. Gerhard. Modern Computer Algebra. Cambridge University Press, second edition, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. von zur Gathen and V. Shoup. Computing Frobenius maps and factoring polynomials. C. Complex., 2(3):187--224, 1992.Google ScholarGoogle ScholarCross RefCross Ref
  18. P. Giorgi, C.-P. Jeannerod, and G. Villard. On the complexity of polynomial matrix computations. In ISSAC'03,pages 135--142. ACM, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. I. Gohberg and V. Olshevsky. Complexity of multiplication with vectors for structured matrices. Linear Algebra Appl., 202:163--192, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  20. O. H. Ibarra, S. Moran, and R. Hui. A generalization of the fast LUP matrix decomposition algorithm and applications. J. Algorithms, 3(1):45--56, 1982.Google ScholarGoogle ScholarCross RefCross Ref
  21. T. Kailath, S. Y. Kung, and M. Morf. Displacement ranks of matrices and linear equations. J. Math. Anal. Appl., 68(2):395--407, 1979.Google ScholarGoogle ScholarCross RefCross Ref
  22. E. Kaltofen. Asymptotically fast solution of Toeplitz-like singular linear systems. In ISSAC'94, pages 297--304. ACM, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. E. Kaltofen. Analysis of Coppersmith's block Wiedemann algorithm for the parallel solution of sparse linear systems. Mathematics of Computation, 64(210):777--806, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. E. Kaltofen and Y. Lakshman. Improved sparse multivariate polynomial interpolation algorithms. In ISSAC'88,volume358 of LNCS. Springer Verlag, 467--474. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. E. Kaltofen and D. Saunders. On Wiedemann's method of solving sparse linear systems. In AAECC-9, volume 539 of LNCS, pages 29--38. Springer Verlag, 1991. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. I. Kaporin. The aggregation and cancellation techniques as a practical tool for faster matrix multiplication. Theor. Comput. Sci., 315(2-3):469--510, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. G. Labahn, D. K. Choi, and S. Cabay. The inverses of block Hankel and block Toeplitz matrices. SIAM J. Comput., 19(1):98--123, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. J. Laderman, V.Y. Pan, and X.-H. Sha. On practical algorithms for accelerated matrix multiplication. Linear Algebra Appl., 162--164:557--588, 1992.Google ScholarGoogle ScholarCross RefCross Ref
  29. D. Lazard. Ideal bases and primary decomposition: the case of two variables. J. Symb. Comput., 1:261--270, 1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. M. Morf. Fast algorithms for multivariable systems.PhD thesis, Stanford University, 1974. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. M. Morf. Doubling algorithms for Toeplitz and related equations. In IEEE Conference on Acoustics, Speech, and Signal Processing, pages 954--959, 1980.Google ScholarGoogle ScholarCross RefCross Ref
  32. T. Mulders. On short multiplications and divisions. AAECC, 11(1):69--88, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  33. M. Nüsken and M. Ziegler. Fast multipoint evaluation of bivariate polynomials. In ESA 2004, number 3222 in LNCS, pages 544--555. Springer, 2004.Google ScholarGoogle Scholar
  34. V. Y. Pan. On computations with dense structured matrices. Math. Comp., 55(191):179--190, 1990.Google ScholarGoogle ScholarCross RefCross Ref
  35. V. Y. Pan. Parametrization of Newton's iteration for computations with structured matrices and applications. Computers Math. Applic., 24(3):61--75, 1992.Google ScholarGoogle ScholarCross RefCross Ref
  36. V. Y. Pan. Structured Matrices and Polynomials. Birkhäuser Boston Inc., 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. V. Y. Pan and A. Zheng. Superfast algorithms for Cauchy-like matrix computations and extensions. Linear Algebra Appl., 310:83--108, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  38. A. Schönhage and V. Strassen. Schnelle Multiplikation großer Zahlen. Computing, 7:281--292, 1971.Google ScholarGoogle ScholarCross RefCross Ref
  39. J. T. Schwartz. Fast probabilistic algorithms for verification of polynomial identities. J. ACM, 27(4):701--717, October 1980. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. A. Storjohann. Algorithms for matrix canonical forms.PhD thesis, ETH, Zürich, 2000.Google ScholarGoogle Scholar
  41. A. Storjohann. Notes on computing minimal approximant bases. Technical report, Symbolic Computation Group, University of Waterloo, 2006.Google ScholarGoogle Scholar
  42. V. Strassen. Gaussian elimination is not optimal. Numerische Mathematik, 13:354--356, 1969.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. M. Van Barel and A. Bultheel. A general module theoretic framework for vector M-Padé and matrix rational interpolation. Numer. Algorithms, 3:451--461, 1992.Google ScholarGoogle ScholarCross RefCross Ref
  44. R. Zippel. Probabilistic algorithms for sparse polynomials. In EUROSAM' 79,volume 72ofLNCS. Springer Verlag, 1979. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. R. Zippel. Interpolating polynomials from their values. J. Symb. Comp., 9(3):375--403, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      ISSAC '07: Proceedings of the 2007 international symposium on Symbolic and algebraic computation
      July 2007
      406 pages
      ISBN:9781595937438
      DOI:10.1145/1277548
      • General Chair:
      • Dongming Wang

      Copyright © 2007 ACM

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      Publication History

      • Published: 29 July 2007

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