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Matrix methods for the simplicial Bernstein representation and for the evaluation of multivariate polynomials

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  • Titi, Jihad
  • Garloff, Jürgen

Abstract

In this paper, multivariate polynomials in the Bernstein basis over a simplex (simplicial Bernstein representation) are considered. Two matrix methods for the computation of the polynomial coefficients with respect to the Bernstein basis, the so-called Bernstein coefficients, are presented. Also matrix methods for the calculation of the Bernstein coefficients over subsimplices generated by subdivision of the standard simplex are proposed and compared with the use of the de Casteljau algorithm. The evaluation of a multivariate polynomial in the power and in the Bernstein basis is considered as well. All the methods solely use matrix operations such as multiplication, transposition, and reshaping; some of them rely also on the bidiagonal factorization of the lower triangular Pascal matrix or the factorization of this matrix by a Toeplitz matrix. The latter one enables the use of the Fast Fourier Transform hereby reducing the amount of arithmetic operations.

Suggested Citation

  • Titi, Jihad & Garloff, Jürgen, 2017. "Matrix methods for the simplicial Bernstein representation and for the evaluation of multivariate polynomials," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 246-258.
    • Handle: RePEc:eee:apmaco:v:315:y:2017:i:c:p:246-258
    DOI: 10.1016/j.amc.2017.07.026
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    References listed on IDEAS

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    1. P. Nataraj & M. Arounassalame, 2011. "Constrained global optimization of multivariate polynomials using Bernstein branch and prune algorithm," Journal of Global Optimization, Springer, vol. 49(2), pages 185-212, February.
    2. de Klerk, E. & den Hertog, D. & Elabwabi, G., 2008. "On the complexity of optimization over the standard simplex," European Journal of Operational Research, Elsevier, vol. 191(3), pages 773-785, December.
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    Cited by:

    1. Titi, Jihad & Garloff, Jürgen, 2019. "Matrix methods for the tensorial Bernstein form," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 254-271.

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