Shape-preserving interpolation by cubic splines

We consider the problem of shape-preserving interpolation by cubic splines. We propose a unified approach to the derivation of sufficient conditions for the k-monotonicity of splines (the preservation of the sign of any derivative) in interpolation of k-monotone data for k = 0, …, 4.     

Shape-preserving interpolation by splines using vector subdivision

We give a local convexity preserving interpolation scheme using parametricC ² cubic splines with uniform knots produced by a vector subdivision scheme which simultaneously provides the function and its first and second order derivatives. This is also adapted to give a scheme which is both local convexity and local monotonicity preserving when the data values are strictly increasing in thex-direction.     

Shape-preserving interpolation by G1 and G2 PH quintic splines

The interpolation of a planar sequence of points p₀, ..., p_Nby shape-preserving G¹ or G² PH quintic splines with specifiedend conditions is considered. The shape-preservation propertyis secured by adjusting ‘tension’ parameters thatarise upon relaxing parametric continuity to geometric continuity.In the G² case, the PH spline construction is based on applyingNewton–Raphson iterations to a global system of equations,commencing with a suitable initialization strategy—thisgeneralizes the construction described previously in NumericalAlgorithms 27, 35–60 (2001). As a simpler and cheaperalternative, a shape-preserving G¹ PH quintic spline schemeis also introduced. Although the order of continuity is lower,this has the advantage of allowing construction through purelylocal equations.     

Some approximation properties of periodic parametric cubic splines

The parametric cubic splines interpolating to such closed curves as the circle and ellipse are derived in a form where their parameters are given by simple algebraic expressions. The structure of these expressions enables the error in approximation of the given curves to be precisely determined and some additional features of the spline deduced.     

The local integro cubic splines and their approximation properties

We show the integro cubic splines proposed by Behforooz [1] can be constructed locally by using B-representation of splines. The approximation properties of the local splines are also considered.     

Discrete weighted cubic splines

This paper presents methods for shape preserving spline interpolation. These methods are based on discrete weighted cubic splines. The analysis results in two algorithms with automatic selection of the shape control parameters: one to preserve the data monotonicity and other to retain the data convexity. Discrete weighted cubic B-splines and control point approximation are also considered.     

Weighted cubic and biharmonic splines

In this paper we discuss the design of algorithms for interpolating discrete data by using weighted cubic and biharmonic splines in such a way that the monotonicity and convexity of the data are preserved. We formulate the problem as a differential multipoint boundary value problem and consider its finite-difference approximation. Two algorithms for automatic selection of shape control parameters (weights) are presented. For weighted biharmonic splines the resulting system of linear equations can be efficiently solved by combining Gaussian elimination with successive over-relaxation method or finite-difference schemes in fractional steps. We consider basic computational aspects and illustrate main features of this original approach.     

Factorization theorems for univariate splines on regular grids

For a given univariate compactly supported distributionφ, we investigate here the spaceS(φ) spanned by its integer translates, the subspaceH(φ) of all exponentials inS(φ) and the kernelK _ϕ of the associated semi-discrete convolutionφ*. The paper addresses a variety of results including a complete structure ofH(φ) andK _ϕ and a characterization of splines of minimal support. The main result shows that eachφ can be expressed asφ = p(∇)τ * M, wherep(∇) is a finite difference operator,τ is a distribution of smaller support satisfyingH(τ) =K _τ = {0}, andM is a spline which depends onH(φ) but not onφ itself, and which in the generic case (termed here “regular”) is the exponential B-spline associated withH(φ). The approach chosen is direct and avoids entirely the Fourier analysis arguments. The fact that a distribution is examined, rather than a function, is essential for the methods employed.     

Convex interval interpolation with cubic splines

A necessary and sufficient criterion is presented under which the problem of the convex interval interpolation with cubicC ¹-splines has at least one solution. The criterion is given as an algorithm which turns out to be effective.Dedicated to Professor Julius Albrecht on the occasion of his 60th birthday.     

Univariate cubic L 1 interpolating splines based on the first derivative and on 5-point windows: analysis, algorithm and shape-preserving properties

In this paper, univariate cubic L ₁ interpolating splines based on the first derivative and on 5-point windows are introduced. Analytical results for minimizing the local spline functional on 5-point windows are presented and, based on these results, an efficient algorithm for calculating the spline coefficients is set up. It is shown that cubic L ₁ splines based on the first derivative and on 5-point windows preserve linearity of the original data and avoid extraneous oscillation. Computational examples, including comparison with first-derivative-based cubic L ₁ splines calculated by a primal affine algorithm and with second-derivative-based cubic L ₁ splines, show the advantages of the first-derivative-based cubic L ₁ splines calculated by the new algorithm.     

Accurate modeling of contact using cubic splines

In this paper, we develop and implement a new method for the accurate representation of contact surfaces. This approach overcomes the difficulties arising from the use of traditional node-to-linear surface contact algorithms. In our proposed method, contact surfaces were modeled accurately using C¹-continuous cubic splines, which interpolate the finite element nodes. In this case, the unit normal vectors are defined uniquely at any point on the contact surfaces. These splines preserve the local deformation of the nodes on each flexible contact surface. Consequently, a consistent linearization of the kinematic contact constraints, based on the spline interpolation, was derived. Moreover, the gap between two contact surfaces was modeled accurately using an efficient surface-to-surface contact search algorithm. Since the continuity of the splines is not affected by the number of nodes, accurate stress distribution can be obtained with less finite elements at the contact surface than that using the traditional linear discretization of the contact surface. Two numerical examples are used to illustrate the advantages of the proposed representation. They show a significant improvement in accuracy compared to traditional piecewise element-based surface interpolation. This approach overcomes the problem of mismatch in a finite element mesh. This is very useful, since most realistic engineering problems involve contact areas that are not known a priori.     

Deficient cubic splines with average slope matching

We obtain a deficient cubic spline function which matches the functions with certain area matching over a greater mesh intervals, and also provides a greater flexibility in replacing area matching as interpolation. We also study their convergence properties to the interpolating functions.     

A shape-preserving approximation by weighted cubic splines

This paper addresses new algorithms for constructing weighted cubic splines that are very effective in interpolation and approximation of sharply changing data. Such spline interpolations are a useful and efficient tool in computer-aided design when control of tension on intervals connecting interpolation points is needed. The error bounds for interpolating weighted splines are obtained. A method for automatic selection of the weights is presented that permits preservation of the monotonicity and convexity of the data. The weighted B-spline basis is also well suited for generation of freeform curves, in the same way as the usual B-splines. By using recurrence relations we derive weighted B-splines and give a three-point local approximation formula that is exact for first-degree polynomials. The resulting curves satisfy the convex hull property, they are piecewise cubics, and the curves can be locally controlled with interval tension in a computationally efficient manner.     

Interpolation and approximation by monotone cubic splines

We study the reconstruction of a function defined on the real line from given, possibly noisy, data values and given shape constraints. Based on two abstract minimization problems characterization results are given for interpolation and approximation (in the euclidean norm) under monotonicity constraints. We derive from these results Newton-type algorithms for the computation of the monotone spline approximant.     

Local quasi-interpolation by cubic C1 splines on type-6 tetrahedral partitions

^** Email: sorokina{at}math.uga.edu^*** Corresponding author. Email: zeilfeld{at}euklid.math.uni-mannheim.de We describe an approximating scheme based on cubic C¹ splineson type-6 tetrahedral partitions using data on volumetric grids.The quasi-interpolating piecewise polynomials are directly determinedby setting their Bernstein–Bézier coefficientsto appropriate combinations of the data values. Hence, eachpolynomial piece of the approximating spline is immediatelyavailable from local portions of the data, without using prescribedderivatives at any point of the domain. The locality of themethod and the uniform boundedness of the associated operatorprovide an error bound, which shows that the approach can beused to approximate and reconstruct trivariate functions. Simultaneously,we show that the derivatives of the quasi-interpolating splinesyield nearly optimal approximation order. Numerical tests withup to 17 x 10⁶ data sites show that the method can be used forefficient approximation.     

Numerical calculation of fourier integrals with cubic splines

The most used formula for calculation of Fourier integrals is Filon's formula which is based on approximation of the function by a quadratic in each double interval. In order to obtain a better approximation we use the cubic spline fit. The method is not restricted to equidistant points, but the final formulas are only derived in this case. Test computations show that the spline formula may be superior to Filon's formula.     

Monotone and convex interpolation by weighted cubic splines

Algorithms for interpolating by weighted cubic splines are constructed with the aim of preserving the monotonicity and convexity of the original discrete data. The analysis performed in this paper makes it possible to develop two algorithms with the automatic choice of the shape-controlling parameters (weights). One of them preserves the monotonicity of the data, while the other preserves the convexity. Certain numerical results are presented.     

Convex interval interpolation with cubic splines,II

The problem of convex interval interpolation with cubicC ¹-splines has an infinite number of solutions, if it is solvable at all. For selecting one of the solutions a regularized mean curvature is minimized. The arising finite dimensional constrained program is solved numerically by means of a dualization approach.Dedicated to Professor Julius Albrecht on the occasion of his 65th birthday.