Approximation with fractal radial basis functions

被引:0
|
作者
Kumar, D. [1 ]
Chand, A. K. B. [1 ]
Massopust, P. R. [2 ]
机构
[1] Indian Inst Technol Madras, Dept Math, Chennai 600036, India
[2] Tech Univ Munich TUM, Dept Math, D-85748 Munich, Germany
关键词
Fractal interpolation functions; Radial basis functions; Strictly positive definite basis function; Shape-preserving approximations; Scattered interpolations; Box dimension; SCATTERED DATA; INTERPOLATION; RECONSTRUCTION; MULTIQUADRICS; SCHEME;
D O I
10.1016/j.cam.2024.116200
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The article reports on the construction of a general class of fractal radial basis functions (RBFs) in the literature. The fractal RBFs is defined through fractal perturbation of a RBF through suitable choice of iterated function system (IFS). A fractal RBF may be smooth depending on the choice of the germ function and the IFS parameters. Characterizations of conditionally strictly positive definite and strictly positive definite fractal functions are studied using the definition of k-times monotonicity. Furthermore, error estimates and shape-preserving properties for the approximants Pj j defined through linear combination of cardinal fractal RBFs are investigated. Several examples are presented to illustrate the convergence of the operator Pj j across various parameters, highlighting the advantages of the fractal approximant Pj j over the corresponding classical operator P . Finally, estimates for the box dimension of the graphs of approximants derived from fractal radial basis functions are given.
引用
下载
收藏
页数:21
相关论文
共 50 条
  • [21] NONLINEAR MODELING AND PREDICTION BY SUCCESSIVE APPROXIMATION USING RADIAL BASIS FUNCTIONS
    HE, XD
    LAPEDES, A
    PHYSICA D, 1994, 70 (03): : 289 - 301
  • [22] Radial basis approximation functions in the boundary element dual reciprocity method
    Partridge, PW
    BOUNDARY ELEMENT TECHNOLOGY XIII: INCORPORATING COMPUTATIONAL METHODS AND TESTING FOR ENGINEERING INTEGRITY, 1999, 2 : 325 - 334
  • [23] Surface approximation of curved data using separable radial basis functions
    Crampton, A
    Mason, JC
    ADVANCED MATHEMATICAL AND COMPUTATIONAL TOOLS IN METROLOGY V, 2001, 57 : 118 - 125
  • [24] Gaussian radial basis functions and the approximation of input-output maps
    Sandberg, IW
    42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS, 2003, : 3635 - 3640
  • [25] PDF-to-ODF inversion by approximation with spherical radial basis functions
    Hielscher, R
    Bernstein, S
    Schaeben, H
    van den Boogaart, KG
    Beckmann, J
    Prestin, J
    ICOTOM 14: TEXTURES OF MATERIALS, PTS 1AND 2, 2005, 495-497 : 313 - 318
  • [26] Modified Radial Basis Functions Approximation Respecting Data Local Features
    Vasta, Jakub
    Skala, Vaclav
    Smolik, Michal
    Cervenka, Martin
    2019 IEEE 15TH INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATICS (INFORMATICS 2019), 2019, : 95 - 99
  • [27] Compact approximation stencils based on integrated flat radial basis functions
    Mai-Duy, N.
    Le, T. T. V.
    Tien, C. M. T.
    Ngo-Cong, D.
    Tran-Cong, T.
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2017, 74 : 79 - 87
  • [28] Behavioral Study of Various Radial Basis Functions for Approximation and Interpolation Purposes
    Cervenka, Martin
    Skala, Vaclav
    2020 IEEE 18TH WORLD SYMPOSIUM ON APPLIED MACHINE INTELLIGENCE AND INFORMATICS (SAMI 2020), 2020, : 135 - 140
  • [29] Gaussian radial basis functions and the approximation of input-output maps
    Sandberg, IW
    INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 2003, 31 (05) : 443 - 452
  • [30] Order-preserving derivative approximation with periodic radial basis functions
    Edward Fuselier
    Grady B. Wright
    Advances in Computational Mathematics, 2015, 41 : 23 - 53