88 research outputs found
Interpolation and scattered data fitting on manifolds using projected PowellāSabin splines
We present methods for either interpolating data or for fitting scattered data on a two-dimensional smooth manifold. The methods are based on a local bivariate Powell-Sabin interpolation scheme, and make use of a family of charts {(UĪ¾ , Ī¾)}Ī¾ā satisfying certain conditions of smooth dependence on Ī¾. If is a C2-manifold embedded into R3, then projections into tangent planes can be employed. The data fitting method is a two-stage method. We prove that the resulting function on the manifold is continuously differentiable, and establish error bounds for both methods for the case when the data are generated by a smooth function
Scattered data fitting on surfaces using projected Powell-Sabin splines
We present C1 methods for either interpolating data or for fitting scattered data associated with a smooth function on a two-dimensional smooth manifold Ī© embedded into R3. The methods are based on a local bivariate Powell-Sabin interpolation scheme, and make use of local projections on the tangent planes. The data fitting method is a two-stage method. We illustrate the performance of the algorithms with some numerical examples, which, in particular, confirm the O(h3) order of convergence as the data becomes dens
Local RBF approximation for scattered data fitting with bivariate splines
In this paper we continue our earlier research [4] aimed at developing effcient methods of local approximation suitable for the first stage of a spline based two-stage scattered data fitting algorithm. As an improvement to the pure polynomial local approximation method used in [5], a hybrid polynomial/radial basis scheme was considered in [4], where the local knot locations for the RBF terms were selected using a greedy knot insertion algorithm. In this paper standard radial local approximations based on interpolation or least squares are considered and a faster procedure is used for knot selection, signicantly reducing the computational cost of the method. Error analysis of the method and numerical results illustrating its performance are given
Transfinite thin plate spline interpolation
Duchon's method of thin plate splines defines a polyharmonic interpolant to
scattered data values as the minimizer of a certain integral functional. For
transfinite interpolation, i.e. interpolation of continuous data prescribed on
curves or hypersurfaces, Kounchev has developed the method of polysplines,
which are piecewise polyharmonic functions of fixed smoothness across the given
hypersurfaces and satisfy some boundary conditions. Recently, Bejancu has
introduced boundary conditions of Beppo Levi type to construct a semi-cardinal
model for polyspline interpolation to data on an infinite set of parallel
hyperplanes. The present paper proves that, for periodic data on a finite set
of parallel hyperplanes, the polyspline interpolant satisfying Beppo Levi
boundary conditions is in fact a thin plate spline, i.e. it minimizes a Duchon
type functional
Basis Functions for Linear-Scaling First-Principles Calculations
In the framework of a recently reported linear-scaling method for
density-functional-pseudopotential calculations, we investigate the use of
localized basis functions for such work. We propose a basis set in which each
local orbital is represented in terms of an array of `blip functions'' on the
points of a grid. We analyze the relation between blip-function basis sets and
the plane-wave basis used in standard pseudopotential methods, derive criteria
for the approximate equivalence of the two, and describe practical tests of
these criteria. Techniques are presented for using blip-function basis sets in
linear-scaling calculations, and numerical tests of these techniques are
reported for Si crystal using both local and non-local pseudopotentials. We
find rapid convergence of the total energy to the values given by standard
plane-wave calculations as the radius of the linear-scaling localized orbitals
is increased.Comment: revtex file, with two encapsulated postscript figures, uses epsf.sty,
submitted to Phys. Rev.
Stable approximation and interpolation with C1 quartic bivariate splines
We show how two recent algorithms for computing C1 quartic interpolating splines can be stabilized to ensure that, for smooth functions, they provide full approximation power with approximation constants depending only on the smallest angle in the triangulation
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