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Generalized barycentric coordinates and approximations of convex functions on arbitrary convex polytopes

机译:任意凸多点面上的广义重心坐标和凸函数的逼近

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In this paper, we study the error in the approximation of a convex function obtained via a one-parameter family of approximation schemes, which we refer to as barycentric approximation schemes. For a given finite set of pairwise distinct points X_n := (X_j)_(i=0)~n in R~d, the barycentric approximation of a convex function/ is of the form: B|f|(x)=nΣi=0 λ_i(x)f(x_i), where (λ_i)_(i=0)~n is a set of barycentric coordinates with respect to the point set X_n. The main content of this paper is two-fold. The first goal is to derive sharp upper and lower bounds on all barycentric coordinates over the convex polytope conv(X_n). The second objective of the paper is to exploit the convexity assumption heavily and establish a number of upper and lower pointwise bounds on the approximation error for approximating arbitrary convex functions. These bounds depend solely on computable quantities related to the data values of the function, the largest and smallest barycentric coordinates. For convex twice continuously differentiable functions, we derive an optimal error estimate. We show that the Delaunay triangulation gives access to efficient algorithms for computing optimal barycentric approximation. Finally, numerical examples are used to show the success of the method.
机译:在本文中,我们研究了通过单参数近似方案族获得的凸函数近似中的误差,我们称其为重心近似方案。对于R〜d中给定的成对的对立点X_n:=(X_j)_(i = 0)〜n的有限集合,凸函数的重心近似形式为:B | f |(x)=nΣi = 0λ_i(x)f(x_i),其中(λ_i)_(i = 0)〜n是相对于点集X_n的重心坐标集。本文的主要内容有两个方面。第一个目标是在凸多面体conv(X_n)上的所有重心坐标上得出清晰的上下边界。本文的第二个目标是大量利用凸度假设,并在近似误差上建立一些上下点界,以近似任意凸函数。这些界限仅取决于与函数的数据值,最大和最小重心坐标有关的可计算量。对于凸的两次连续可微函数,我们导出了最佳误差估计。我们证明了Delaunay三角剖分可以访问有效的算法,以计算最佳重心近似值。最后,通过算例说明了该方法的成功。

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