Abstract
Given discrete function values sampled at uniform centers, the iterated quasi-interpolation approach for approximating the m th derivative consists of two steps. The first step adopts m successive applications of the operator DQ (the quasi-interpolation operator Q first, and then the differentiation operator D) to get approximated values of the m th derivative at uniform centers. Then, by one further application of the quasi-interpolation operator Q to corresponding approximated derivative values gives the final approximation of the m th derivative. The most salient feature of the approach is that it approximates all derivatives with the same convergence rate. In addition, it is valid for a general multivariate function, compared with the existing iterated interpolation approaches that are only valid for periodic functions, so far. Numerical examples of approximating high-order derivatives using both the iterated and direct approach based on B-spline quasi-interpolation and multiquadric quasi-interpolation are presented at the end of the paper, which demonstrate that the iterated quasi-interpolation approach provides higher approximation orders than the corresponding direct approach.
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References
Beatson, R., Dyn, N.: Multiquadric B-splines. J. Approx. Theory 87, 1–24 (1996)
Beatson, R., Powell, M.: Univariate multiquadric approximation: quasi-interpolation to scattered data. Constr. Approx. 8, 275–288 (1992)
Buhmann, M.: Convergence of univariate quasi-interpolation using multiquadrics. IMA J. Numer. Anal. 8, 365–383 (1988)
Buhmann, M.: On quasi-interpolation with radial basis functions. J. Approx. Theory 72, 103–130 (1993)
Buhmann, M.: Radial Basis Functions: Theory and Implementations. Cambridge University Press, UK (2004)
Buhmann, M.: On quasi-interpolation by radial basis function with scattered centers. Construct. Approx. 11, 239–254 (1995)
Buhmann, M., Dai, F.: Pointwise approximation with quasi-interpolation by radial basis functions. J. Approx. Theory 192, 156–192 (2015)
Cecil, T., Qian, J., Osher, S.: Numerical methods for high dimensional Hamiltonian-Jocabian equations using radial basis functions. J. Comput. Phys. 196, 327–347 (2004)
Cheney, E.: Introduction to Approximation Theory, 2nd edn. Chelsea, New York (1982)
Davydov, O., Schaback, R.: Error bounds for kernel-based numerical differentiation. Numer. Math. 132, 243–269 (2016)
Davydov, O., Schaback, R.: Minimal numerical differentiation formulas. Numer. Math. 140, 555–592 (2018)
Davydov, O., Schaback, R.: Optimal stencils in Sobolev spaces. IMA J. Numer. Anal. 39, 398–422 (2019)
Fasshauer, G.E.: Meshfree approximation methods with MATLAB. World Scientific Publishing Co. Pte. Ltd (2007)
Franke, R.: Scattered data intepolations: tests of some methods. Math. Comp. 38, 181–200 (1982)
Foucher, F., Sablonniére, P.: Approximating partial derivatives of first and second order by quadratic spline quasi-interpolants on uniform meshes. Math. Comput. Simul. 77, 202–208 (2008)
Fuselier, E., Wright, G.: A high-order kernel method for diffusion and reaction-diffusion equations on surfaces. J. Sci. Comput. 56, 535–565 (2013)
Fuselier, E., Wright, G.: Order-preserving derivative approximation with periodic radial basis functions. Adv. Comput. Math. 41, 23–53 (2015)
Gao, W.W., Wu, Z.M.: A quasi-interpolation scheme for periodic data based on multiquadric trigonometric B-splines. J. Comput. Appl. Math. 271, 20–30 (2014)
Gao, W.W., Wu, Z.M.: Approximation orders and shape preserving properties of the multiquadric trigonometric B-spline quasi-interpolant. Comput. Math. Appl. 69, 696–707 (2015)
Gasser, T., Müller, H.: Estimating regression functions and their derivatives by the kernel method. Scandinavian J. Statis. 11, 171–185 (1984)
Grohs, P.: Quasi-interpolation in Riemannian manifolds. IMA J. Numer. Anal. 33, 849–874 (2013)
Jetter, K., Zhou, D.X.: Order of linear approximation from shift-invariant spaces. Construct. Approx. 11, 423–438 (1995)
Jia, R.Q., Lei, J.J.: A new version of Strang-Fix conditions. J. Approx. Theory 74, 221–225 (1993)
Light, W.A., Cheney, E.W.: Quasi-interpolation with translates of a function having noncompact support. Construct. Approx. 8, 35–48 (1992)
Ling, L.: Finding numerical derivatives for unstructured and noisy data by multiscale kernels. SIAM J. Numer. Anal. 44, 1780–1800 (2006)
Ma, L.M., Wu, Z.M.: Approximation to the k-th derivatives by multiquadric quasi-intepolation method. J. Comp. Appl. Math. 2, 925–932 (2009)
Ma, L.M., Wu, Z.M.: Stability of multiquadric quasi-interpolation to approximate high order derivatives. Sci. China Math. 53, 985–992 (2010)
Narcowich, F.J., Schaback, R., Ward, J.D.: Approximation in Sobolev spaces by kernel expansions. J. Approx. Theory 114, 70–83 (2002)
Narcowich, F.J., Sun, X.P., Ward, J.D., Wendland, H.: Direct and inverse Sobolev error estimates for scattered data interpolation via spherical basis functions. Found. Comput. Math. 7, 369–390 (2007)
Narcowich, F.J., Rowe, S.T., Ward, J.D.: A novel Galerkin method for solving PDES on the sphere using highly localized kernel bases. Math. Comput. 86, 197–231 (2017)
Plonka, G., Tasche, M.: Prony methods for recovery of structured functions. GAMM-Mitt. 37, 239–258 (2014)
Potts, D., Tasche, M.: Parameter estimation for nonincreasing sums by Prony-like methods. Linear Algebra Appl. 439, 1024–1039 (2013)
Rabut, C.: An introduction to Schoenberg’s approximation. Comput. Math. Appl. 24, 139–175 (1991)
Ramming, T., Wendland, H.: Kernel-based discretization method for first order patrial differential equations. Math. Comput. 87, 1757–1781 (2018)
Schaback, R., Wu, Z.M.: Construction techniques for highly accurate quasi-interpolation operators. J. Approx. Theory 91, 320–331 (1997)
Schumaker, L.: Spline Functions: Basic Theory, 3rd edn. Cambridge University Press, NewYork (2007)
Shelley, M.J., Baker, G.: Order-preserving approximations to successive derivatives of periodic functions by iterated splines. SIAM J. Numer. Anal. 25, 1442–1452 (1988)
Shu, C., Ding, H., Yeo, K.S.: Local radial basis function-based differential quadrature method and its application to solve two-dimensional incompressible Navier-Stokes equations. Comput. Methods Appl. Mech. Eng. 192, 941–954 (2003)
Smith, P.W., Ward, J.D.: Quasi-interpolants from spline interpolation operators. Construct. Approx. 6, 97–110 (1990)
Stein, E., Weiss, G.: Introduction to Fourier Analysis on Euclidean Spaces. Princeton Univ. Press, Princeton (1971)
Fix, G., Strang G.: A Fourier analysis of the finite element method. Constructive Aspects of Functional Analysis, CIME I 1, 793–840 (1970)
Vainikko, E., Vainikko, G.: A spline product quasi-interpolation method for weakly singular Fredholm integral equations. SIAM J. Numer. Anal. 46, 1799–1820 (2008)
Wahba, G.: Smoothing noisy data with spline functions. Numer. Math. 24, 383–393 (1975)
Wei, T., Hon, Y.C., Cheng, J.: Reconstruction of numerical derivatives from scattered noisy data. Inverse Probl. 21, 657–672 (2005)
Wright, G.B.: Radial Basis Function Interpolation: Numerical and Analytical Developments. PhD. Thesis, University of Colorado, Boulder (2003)
Wu, Z.M., Schaback, R.: Shape preserving properties and convergence of univariate multiquadric quasi-interpolation. Acta Math. Appl. Sin. 10, 441–446 (1994)
Wu, Z.M., Liu, J.P.: Generalized Strang-Fix condition for scattered data quasi-interpolation. Adv. Comput. Math. 23, 201–214 (2005)
Wu, Z.M., Sun, X.P., Ma, L.M.: Sampling scattered data with Bernstein polynomials: stochastic and deterministic error estimates. Adv. Comput. Math. 38, 187–205 (2013)
Wu, Z.M., Zhang, R.: Learning physics by data for the motion of a sphere falling in a non-Newtonian fluid. Commun. Nonlinear Sci. Numer. Simul. 67, 577–593 (2019)
Zhu, C.G., Wang, R.H.: Numerical solution of Burgers’ equation by cubic B-spline quasi-interpolation. Appl. Math. Comput. 208, 260–272 (2009)
Acknowledgments
We are grateful to the editor and the referee for insightful comments and valuable suggestions that helped us to improve the presentation of the manuscript.
Funding
This work is supported by NSFC (11871074, 11501006, 61672032), NSFC Key Project (11631015,91330201), Hong Kong Scholars Program (2018046), SGST (12DZ 2272800), Fund of Introducing Leaders of Science and Technology of Anhui University (J10117700057), the 4th Project of Cultivating Backbone of Young Teachers of Anhui University (J01005138), and Anhui Provincial Science and Technology Major Project (16030701091).
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Sun, Z., Wu, Z. & Gao, W. An iterated quasi-interpolation approach for derivative approximation. Numer Algor 85, 255–276 (2020). https://doi.org/10.1007/s11075-019-00812-9
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DOI: https://doi.org/10.1007/s11075-019-00812-9