Shape preserving rational cubic trigonometric fractal interpolation functions

被引:11
|
作者
Tyada, K. R. [1 ,3 ]
Chand, A. K. B. [1 ]
Sajid, M. [2 ]
机构
[1] Indian Inst Technol Madras, Dept Math, Chennai 600036, Tamil Nadu, India
[2] Qassim Univ, Coll Engn, Dept Mech Engn, Buraydah 51452, Al Qassim, Saudi Arabia
[3] Sri Sathya Sai Inst Higher Learning, Dept Math & Comp Sci, Bangalore 560067, Karnataka, India
关键词
Iterated function systems; Fractal interpolation; Rational cubic trigonometric interpolation; Peano-Kernel; Constrained interpolation; Positivity; Monotonicity; POSITIVITY; POLYNOMIALS;
D O I
10.1016/j.matcom.2021.06.015
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
B.V This paper is devoted to a hierarchical approach of constructing a class of fractal interpolants with trigonometric basis functions and to preserve the geometric behavior of given univariate data set by these fractal interpolants. In this paper, we propose a new family of C-1-rational cubic trigonometric fractal interpolation functions (RCTFIFs) that are the generalized fractal version of the classical rational cubic trigonometric polynomial spline of the form p(i)(theta)/q(i)(theta), where p(i)(theta) and q(i)(theta) are cubic trigonometric polynomials with four shape parameters in each sub-interval. The convergence of the RCTFIF towards the original function in C-3 is studied. We deduce the simple data dependent sufficient conditions on the scaling factors and shape parameters associated with the C-1-RCTFIF so that the proposed RCTFIF lies above a straight line when the interpolation data set is constrained by the same condition. The first derivative of the proposed RCTFIF is irregular in a finite or dense subset of the interpolation interval and matches with the first derivative of the classical rational trigonometric cubic interpolation function whenever all scaling factors are zero. The positive shape preservation is a particular case of the constrained interpolation. We derive sufficient conditions on the trigonometric IFS parameters so that the proposed RCTFIF preserves the monotone or comonotone feature of prescribed data. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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页码:866 / 891
页数:26
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