Parameter Identification of Constrained Data by a New Class of Rational Fractal Function

Abstract

This paper sets a theoretical foundation for the applications of the fractal interpolation functions (FIFs). We construct rational cubic spline FIFs (RCSFIFs) with quadratic denominator involving two shape parameters. The elements of the iterated function system (IFS) in each subinterval are identified befittingly so that the graph of the resulting C 1 -RCSFIF lies within a prescribed rectangle. These parameters include, in particular, conditions on the positivity of the C 1 -RCSFIF. The problem of visualization of constrained data is also addressed when the data is lying above a straight line, the proposed fractal curve is required to lie on the same side of the line. We illustrate our interpolation scheme with some numerical examples.

Bicubic partially blended rational quartic surface

“…Thus researchers keep trying to find best possible function that can interpolate the data with shape preserving property. As a submissive contribution to this goal, Chand and coworkers have initiated the study on shape preserving fractal interpolation and approximation using various families of polynomial and rational IFSs (see, for instance, [12,13,14,15,16,17,18,19]). These shape preserving fractal interpolation schemes possess the novelty that the interpolants inherit the shape property in question and at the same time the suitable derivatives of these interpolants own irregularity in finite or dense subsets of the interpolation interval.…”