Error estimates for scattered data interpolation on spheres

We study Sobolev type estimates for the approximation order resulting from using strictly positive definite kernels to do interpolation on the -sphere. The interpolation knots are scattered. Our approach partly follows the general theory of Golomb and Weinberger and related estimates. These error estimates are then based on series expansions of smooth functions in terms of spherical harmonics. The Markov inequality for spherical harmonics is essential to our analysis and is used in order to find lower bounds for certain sampling operators on spaces of spherical harmonics.

     

The Appell interpolation problem

A general linear interpolation problem is considered. We will call it the Appell interpolation problem because the solution can be expressed by a basis of Appell polynomials. Some classical and non-classical examples are also considered. Finally, numerical calculations are given.     

A kind of multiquadric quasi-interpolation operator satisfying any degree polynomial reproduction property to scattered data

In this paper, by virtue of using the linear combinations of the shifts of f(x) to approximate the derivatives of f(x) and Waldron’s superposition idea (2009), we modify a multiquadric quasi-interpolation with the property of linear reproducing to scattered data on one-dimensional space, such that a kind of quasi-interpolation operator L_r+1f has the property of r+1(r∈Z,r≥0) degree polynomial reproducing and converges up to a rate of r+2. There is no demand for the derivatives of f in the proposed quasi-interpolation L_r+1f, so it does not increase the orders of smoothness of f. Finally, some numerical experiments are shown to compare the approximation capacity of our quasi-interpolation operators with that of Wu-Schaback’s quasi-interpolation scheme and Feng-Li’s quasi-interpolation scheme.     

A note on stability results for scattered data interpolation on Euclidean spheres

The present work considers the interpolation of the scattered data on the d-sphere by spherical polynomials. We prove bounds on the conditioning of the problem which rely only on the separation distance of the sampling nodes and on the degree of polynomials being used. To this end, we establish a packing argument for well separated sampling nodes and construct strongly localized polynomials on spheres. Numerical results illustrate our theoretical findings. Dedicated to Professor Manfred Tasche on the occasion of his 65th birthday.     

On Radon’s recipe for choosing correct sites for multivariate polynomial interpolation

A class of sets correct for multivariate polynomial interpolation is defined and verified, and shown to coincide with the collection of all correct sets constructible by the recursive application of Radon’s recipe, and a recent concrete recipe for correct sets is shown to produce elements in that class.     

曲面上离散点集的光滑插值

本文主要解决了如下问题：给定Ｒ３凸曲面上的任意个离散点｛Ｐｉ｝Ｎｉ＝１及其对应的函数值｛ｆｉ｝Ｎｉ＝１，要求构造曲面上的插值函数ｆ（ｘ），使得ｆ（Ｐｉ）＝ｆｉ，（ｉ＝１，２，…，Ｎ）．本文方法推广了球面上离散点集的Ｍｕｌｔｉｑｕａｄｒｉｃ插值方法，并且对分区域插值方法也给予了讨论．     

Approximating scattered data with discontinuities

A method is presented for approximating scattered data by a function defined on a regular two-dimensional grid. It is required that the approximation is discontinuous across given curves in the parameter domain known as faults. The method has three phases: regularisation, local approximation and extrapolation. The main emphasis is put on the extrapolation which is based on a matrix equation which minimises second order differences. By approximating each fault by a set of line segments parallel with one of the axes, it is simple to introduce natural boundary conditions across the faults. The resulting approximation has, as expected, discontinuities across faults and is smooth elsewhere. The method is stable even for large data sets.This research was supported by the Royal Norwegian Council for Scientific and Industrial Research.     

Computing Fekete and Lebesgue points: Simplex, square, disk

We have computed point sets with maximal absolute value of the Vandermonde determinant (Fekete points) or minimal Lebesgue constant (Lebesgue points) on three basic bidimensional compact sets: the simplex, the square, and the disk. Using routines of the Matlab Optimization Toolbox, we have obtained some of the best bivariate interpolation sets known so far.     

Scattered and track data interpolation using an efficient strip searching procedure

A new local algorithm for bivariate interpolation of large sets of scattered and track data is presented. The method, which changes partially depending on the kind of data, is based on the partition of the interpolation domain in a suitable number of parallel strips, and, starting from these, on the construction for any data point of a square neighbourhood containing a convenient number of data points. Then, the well-known modified Shepard’s formula for surface interpolation is applied with some effective improvements. The proposed algorithm is very fast, owing to the optimal nearest neighbour searching, and achieves good accuracy. Computational cost and storage requirements are analyzed. Moreover, the efficiency and reliability of the algorithm are shown by several numerical tests, also performed by Renka’s algorithm for a comparison.     

Thinning algorithms for scattered data interpolation

Multistep interpolation of scattered data by compactly supported radial basis functions requires hierarchical subsets of the data. This paper analyzes thinning algorithms for generating evenly distributed subsets of scattered data in a given domain in ℝ ^d .     

C^1保单调有理二次插值

本文提供一类保单调分段有理二次插值方法。插值公式具有两个可调的形状参数。逼近精度为Ｏ（ｈ＾２）。     

An analysis of wavelet frame based scattered data reconstruction

In real world applications many signals contain singularities, like edges in images. Recent wavelet frame based approaches were successfully applied to reconstruct scattered data from such functions while preserving these features. In this paper we present a recent approach which determines the approximant from shift invariant subspaces by minimizing an ${?}_1$-regularized least squares problem which makes additional use of the wavelet frame transform in order to preserve sharp edges. We give a detailed analysis of this approach, i.e., how the approximation error behaves dependent on data density and noise level. Moreover, a link to wavelet frame based image restoration models is established and the convergence of these models is analyzed. In the end, we present some numerical examples, for instance how to apply this approach to handle coarse-grained models in molecular dynamics.     

Monotone interpolation of scattered data in R s

We present a method to interpolate scattered monotone data in R ^s using a variational approach. We present both theoretical and practical properties and give a dual algorithm allowing us to compute the resulting function whens=2. The method is specially suited for scattered data but comparison with existing methods for data on grids shows that it is a valid approach even in that case.Communicated by Wolfgang Dahmen.     

Comonotone parametric C1 interpolation of nongridded data

We present a local scheme for constructing a C¹ interpolating function comonotone with a set of data having a tensor product topology. The constructed interpolant is a parametric surface with piecewise bicubic components which locally maintain the monotonicity of the data along curves “parallel” to the related coordinate lines. Error estimates and graphical examples are provided.     

The convergence of three spline methods for scattered data interpolation and fitting

The convergences of three L₁ spline methods for scattered data interpolation and fitting using bivariate spline spaces are studied in this paper. That is, L₁ interpolatory splines, splines of least absolute deviation, and L₁ smoothing splines are shown to converge to the given data function under some conditions and hence, the surfaces from these three methods will resemble the given data values.     

On cardinal sequences of scattered spaces

It was proved by Dow and Simon that there are 2^ω₁ (as many as possible) pairwise nonhomeomorphic compact, T₂, scattered spaces of height ω₁ and width ω. In this paper, we prove that if is an ordinal withω₁ < ω₂ and θ = κ_ξ: ξ < is a sequence of cardinals such that either κ_ξ = ω or κ_ξ = ω₁ for every ξ < , then there are 2^ω₁ pairwise nonhomeomorphic compact, T₂, scattered spaces whose cardinal sequence is θ.     

Polynomial approximation on the sphere using scattered data

We consider the problem of approximately reconstructing a function f defined on the surface of the unit sphere in the Euclidean space ℝ^{q +1} by using samples of f at scattered sites. A central role is played by the construction of a new operator for polynomial approximation, which is a uniformly bounded quasi‐projection in the de la Vallée Poussin style, i.e. it reproduces spherical polynomials up to a certain degree and has uniformly bounded L^p operator norm for 1 ≤ p ≤ ∞. Using certain positive quadrature rules for scattered sites due to Mhaskar, Narcowich and Ward, we discretize this operator obtaining a polynomial approximation of the target function which can be computed from scattered data and provides the same approximation degree of the best polynomial approximation. To establish the error estimates we use Marcinkiewicz–Zygmund inequalities, which we derive from our continuous approximating operator. We give concrete bounds for all constants in the Marcinkiewicz–Zygmund inequalities as well as in the error estimates. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

C1 rational quadratic spline interpolation to convex data

For a set of convex data we find conditions for the convexity of the rational quadratic spline interpolation. As an application, we prove for several functions that if the data derives from one of these functions, then the above convexity conditions are verified.