Elements of Bi-cubic Polynomial Natural Spline Interpolation for Scattered Data: Boundary Conditions Meet Partition of Unity Technique

  • Weizhi Xu
Keywords: Scattered Data Interpolation, Bi-cubic Polynomial, Partition of Unity, Natural Spline, Boundary Condition

Abstract

This paper investigates one kind of interpolation for scattered data by bi-cubic polynomial natural spline, in which the integral of square of partial derivative of two orders to x and to y for the interpolating function is minimal (with natural boundary conditions). Firstly, bi-cubic polynomial natural spline interpolations with four kinds of boundary conditions are studied. By the spline function methods of Hilbert space, their solutions are constructed as the sum of bi-linear polynomials and piecewise bi-cubic polynomials. Some properties of the solutions are also studied. In fact, bi-cubic natural spline interpolation on a rectangular domain is a generalization of the cubic natural spline interpolation on an interval. Secondly, based on bi-cubic polynomial natural spline interpolations of four kinds of boundary conditions, and using partition of unity technique, a Partition of Unity Interpolation Element Method (PUIEM) for fitting scattered data is proposed. Numerical experiments show that the PUIEM is adaptive and outperforms state-of-the-art competitions, such as the thin plate spline interpolation and the bi-cubic polynomial natural spline interpolations for scattered data.

References

J. Ahlberg, E. Nilson and J. Walsh, The Theory of Splines and Their Applications, Academic Press, New York, 1967.

C. de Boor, A Practical Guide to Splines, Springer Verlag Publishers, 2001.

S. Kersey and M. Lai, Convergence of Local Variational Spline Interpolation, Journal of Computational Analysis and Applications, 341: 398-415, 2008.

R. Wang, Multivariate Spline Functions and Their Applications, Kluwer Academic Publishers, The Netherlands, 2001.

G. Nurnberger and F. Zeilfelder, Developments in bivariate spline interpolation, Journal of Computational and Applied Mathematics, 121:125-152, 2000.

M. Lai and L. Schumaker, Spline Functions Over Triangulations, London: Cambridge University Press, 2007.

T. Zhou, D. Han and M. Lai, Energy Minimization Method for Scattered Data Hermit Interpolation, Applied Numerical Mathematics, 58: 646-659,2008.

M. Lai, Multivarariate Splines for Data Fitting and Approximation, Approximation Theory XII, San Antonio, 2007, edited by M. Neamtu and L.L.Schumaker, Brentwood: Nashboro Press, 2008: 210-228, 2008.

L. Guan and Y. Li, Multivariate polynomial natural spline interpolation to scattered data, Academic Press, New York, 1989.

C. Chui and L. Guan, Multivariate polynomial natural splines for interpolation of scattered data and other applications, World Scientific Pub, Singapore, 1993.

L. Guan and B. Liu, Surface Design by Natural Splines Over Refined Grid Points, Journal of Computational and Applied

Mathematics, 163(1):107-115, 2004.

A. Bezhaev and V. Vasilenko, Variational Theory of Splines, Kluwer Academic/Plenum Publishers, New York, 2001.

L. Guan, W. Xu and Q. Zhu, Interpolation for Space Scattered Data by Bicubic Polynomial Natural Splines, Acta Scientiarum Naturalium Universitatis Sunyatseni, 47(5): 1-4, 2008.

J. Melenk and I. Babuka, The partition of unity finite element method: basic theory and applications, Computer Methods in Applied Mechanics and Engineering, 139: 289-314, 1996.

I. Babuka, U. Banerjee and J. Osborn, Generalized finite element methods: main ideas, result and perspective, International Journal of Computational Methods, 1(1): 67-103, 2004.

K. Segeth, Some splines produced by smooth interpolation, Applied Mathematics and Computation, 319: 387-394, 2018.

H. Johnson and M. Johnson, Quasi-elastic cubic splines in Rd, Computer Aided Geometric Design, 81: 101893, 2020.

K. Gao, G. Mei, S. Cuomo, F. Piccialli and N. Xiong, Adaptive RBF interpolation for estimating missing values in geographical data, Available at http://arxiv.org/abs/1908.03690, 2019.

Published
2020-12-02
How to Cite
Xu, W. (2020). Elements of Bi-cubic Polynomial Natural Spline Interpolation for Scattered Data: Boundary Conditions Meet Partition of Unity Technique. Statistics, Optimization & Information Computing, 8(4), 994-1010. https://doi.org/10.19139/soic-2310-5070-1083
Section
Research Articles