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A new class of rational cubic spline fractal interpolation function and its constrained aspects

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TLDR
This paper constructs a new class of rational cubic spline FIFs (RCSFIFs) with a preassigned quadratic denominator with two shape parameters, which includes classical rational cubic interpolant [Appl. Comp., 216 (2010), pp. 2036–2049] as special case and improves the sufficient conditions for positivity.
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This article is published in Applied Mathematics and Computation.The article was published on 2019-04-01. It has received 18 citations till now. The article focuses on the topics: Interpolation & Piecewise.

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Citations
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Fractal Calculus on Fractal Interpolation Functions

TL;DR: In this paper, the Fα-calculus is implemented on fractal interpolation functions and Weierstrass functions, which may be non-differentiable and non-integrable in the sense of ordinary calculus.
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Shape preserving rational quartic fractal functions

TL;DR: The appearance of fractal interpolation function represents a revival of experimental mathematics, raised by computers and intensified by powerful evidence of its applications as mentioned in this paper, and it represents a new direction for experimental mathematics.
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Shape preserving rational cubic trigonometric fractal interpolation functions

TL;DR: A new family of C 1 -rational cubic trigonometric fractal interpolation functions (RCTFIFs) that are the generalized fractal version of the classical rational cubic trig onometric polynomial spline of the form p i ( θ ) ∕ q i (θ ) , where p i and q i are cubic trigonal polynomials with four shape parameters in each sub-interval.
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Multivariate Affine Fractal Interpolation

TL;DR: Fractal interpolation functions capture the irregularity of some data very effectively in comparison with the classical interpolants as discussed by the authors, and yield a new technique for fitting experimental data sample.
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Construction of cubic spline hidden variable recurrent fractal interpolation function and its fractional calculus

TL;DR: In this paper, a cubic spline hidden variable recurrent fractal interpolation function (CSHVRFIF) is constructed and its Riemann-Liouville fractional integral and derivative are also HRLFIFs.
References
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Journal ArticleDOI

Monotone Piecewise Cubic Interpolation

TL;DR: In this article, a monotone piecewise bicubic interpolation algorithm was proposed for data on a rectangular mesh, where the first partial derivatives and first mixed partial derivatives are determined by the mesh points.
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Fractal Functions and Interpolation

TL;DR: In this article, the authors introduce iterated function systems whose attractorsG are graphs of continuous functionsf∶I→R, which interpolate the data according tof(x��i)=y fixmei fori e {0,1,⋯,N}.
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The calculus of fractal interpolation functions

TL;DR: The calculus of deterministic fractal functions is introduced in this article, which can be explicitly indefinitely integrated any number of times, yielding a hierarchy of successively smoother interpolation functions which generalize splines and which are attractors for iterated function systems.
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Piecewise rational quadratic interpolation to monotonic data

TL;DR: In this paper, an explicit representation of a piecewise rational quadratic function is developed which produces a monotonic interpolant to given monotonicity data. But this method is not suitable for the case of complex data.
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Positivity of cubic polynomials on intervals and positive spline interpolation

TL;DR: In this paper, a criterion for the positivity of a cubic polynomial on a given interval is derived, and a necessary and sufficient condition is given under which cubicC 1-spline interpolants are nonnegative.
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