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Spline Approximation, Part 2: From Polynomials in the Monomial Basis to B-splines—A Derivation

Author

Listed:
  • Nikolaj Ezhov

    (Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany)

  • Frank Neitzel

    (Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany)

  • Svetozar Petrovic

    (Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany
    Section 1.2: Global Geomonitoring and Gravity Field, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany)

Abstract

In a series of three articles, spline approximation is presented from a geodetic point of view. In part 1, an introduction to spline approximation of 2D curves was given and the basic methodology of spline approximation was demonstrated using splines constructed from ordinary polynomials. In this article (part 2), the notion of B-spline is explained by means of the transition from a representation of a polynomial in the monomial basis (ordinary polynomial) to the Lagrangian form, and from it to the Bernstein form, which finally yields the B-spline representation. Moreover, the direct relation between the B-spline parameters and the parameters of a polynomial in the monomial basis is derived. The numerical stability of the spline approximation approaches discussed in part 1 and in this paper, as well as the potential of splines in deformation detection, will be investigated on numerical examples in the forthcoming part 3.

Suggested Citation

  • Nikolaj Ezhov & Frank Neitzel & Svetozar Petrovic, 2021. "Spline Approximation, Part 2: From Polynomials in the Monomial Basis to B-splines—A Derivation," Mathematics, MDPI, vol. 9(18), pages 1-24, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2198-:d:631413
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    References listed on IDEAS

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    1. Frank Neitzel & Nikolaj Ezhov & Svetozar Petrovic, 2019. "Total Least Squares Spline Approximation," Mathematics, MDPI, vol. 7(5), pages 1-20, May.
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    Cited by:

    1. Yanchun Zhao & Mengzhu Zhang & Qian Ni & Xuhui Wang, 2023. "Adaptive Nonparametric Density Estimation with B-Spline Bases," Mathematics, MDPI, vol. 11(2), pages 1-12, January.
    2. Sergei Aliukov & Anatoliy Alabugin & Konstantin Osintsev, 2022. "Review of Methods, Applications and Publications on the Approximation of Piecewise Linear and Generalized Functions," Mathematics, MDPI, vol. 10(16), pages 1-43, August.

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