250 research outputs found
Shape preserving approximation using least squares splines
Least squares polynomial splines are an effective tool for data fitting, but they may fail to preserve essential properties of the underlying function, such as monotonicity or convexity. The shape restrictions are translated into linear inequality conditions on spline coefficients. The basis functions are selected in such a way that these conditions take a simple form, and the problem becomes non-negative least squares problem, for which effecitive and robust methods of solution exist. Multidimensional monotone approximation is achieved by using tensor-product splines with the appropriate restrictions. Additional inter polation conditions can also be introduced. The conversion formulas to traditional B-spline representation are provided. <br /
A tension approach to controlling the shape of cubic spline surfaces on FVS triangulations
We propose a parametric tensioned version of the FVS macro-element to control the shape of the composite surface and remove artificial oscillations, bumps and other undesired behaviour. In particular, this approach is applied to C1 cubic spline surfaces over a four-directional mesh produced by two-stage scattered data fitting methods
Recent Results on Near-Best Spline Quasi-Interpolants
Roughly speaking, a near-best (abbr. NB) quasi-interpolant (abbr. QI) is an
approximation operator of the form where the 's are B-splines and the 's
are linear discrete or integral forms acting on the given function . These
forms depend on a finite number of coefficients which are the components of
vectors for . The index refers to this sequence of
vectors. In order that for all polynomials belonging to some
subspace included in the space of splines generated by the 's, each
vector must lie in an affine subspace , i.e. satisfy some
linear constraints. However there remain some degrees of freedom which are used
to minimize for each . It is easy to
prove that is an upper bound of
: thus, instead of minimizing the infinite norm of
, which is a difficult problem, we minimize an upper bound of this norm,
which is much easier to do. Moreover, the latter problem has always at least
one solution, which is associated with a NB QI. In the first part of the paper,
we give a survey on NB univariate or bivariate spline QIs defined on uniform or
non-uniform partitions and already studied by the author and coworkers. In the
second part, we give some new results, mainly on univariate and bivariate
integral QIs on {\sl non-uniform} partitions: in that case, NB QIs are more
difficult to characterize and the optimal properties strongly depend on the
geometry of the partition. Therefore we have restricted our study to QIs having
interesting shape properties and/or infinite norms uniformly bounded
independently of the partition
Totally positive refinable functions with general dilation M
We construct a new class of approximating functions that are M-refinable and provide shape preserving approximations. The refinable functions in the class are smooth, compactly supported, centrally symmetric and totally positive. Moreover, their refinable masks are associated with convergent subdivision schemes. The presence of one or more shape parameters gives a great flexibility in the applications. Some examples for dilation M=4and M=5are also given
Staircase algorithm and construction of convex spline interpolants up to the continuity C3
AbstractThis paper is concerned with the convex interpolation of data sets. Based on the staircase algorithm, several methods are presented which allow the construction of convex spline interpolants up to the continuity C3
Continuous State Dynamic Programming via Nonexpansive Approximation
This paper studies fitted value iteration for continuous state dynamic programming using nonexpansive function approximators. A number of nonexpansive approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.Dynamic Programming; Approximation
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