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Subdivision Schemes of Sets and the Approximation of Set-Valued Functions in the Symmetric Difference Metric

机译:对称差分度量中的集细分方案和集值函数的逼近

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In this work we construct subdivision schemes refining general subsets of ?n and study their applications to the approximation of set-valued functions. Differently from previous works on set-valued approximation, our methods are developed and analyzed in the metric space of Lebesgue measurable sets endowed with the symmetric difference metric. The construction of the set-valued subdivision schemes is based on a new weighted average of two sets, which is defined for positive weights (corresponding to interpolation) and also when one weight is negative (corresponding to extrapolation). Using the new average with positive weights, we adapt to sets spline subdivision schemes computed by the Lane-Riesenfeld algorithm, which requires only averages of pairs of numbers. The averages of numbers are then replaced by the new averages of pairs of sets. Among other features of the resulting set-valued subdivision schemes, we prove their monotonicity preservation property. Using the new weighted average of sets with both positive and negative weights, we adapt to sets the 4-point interpolatory subdivision scheme. Finally, we discuss the extension of the results obtained in metric spaces of sets, to general metric spaces endowed with an averaging operation satisfying certain properties.
机译:在这项工作中,我们构造细分方案来细化?n的一般子集,并研究它们在逼近设定值函数中的应用。与先前关于集值逼近的工作不同,我们的方法是在赋予对称差分度量的Lebesgue可测集的度量空间中发展和分析的。集值细分方案的构造基于两组的新加权平均值,这是针对正权重(对应于插值)以及当一个权重为负(对应于外推)时定义的。使用具有正权重的新平均值,我们适应由Lane-Riesenfeld算法计算的集样条细分方案,该方案仅需要数对的平均值。然后,将数字的平均值替换为集合对的新平均值。在所得集值细分方案的其他特征中,我们证明了它们的单调性保持特性。使用具有正和负权重的新的加权平均集,我们适应于设置4点插值细分方案。最后,我们讨论将在集合的度量空间中获得的结果扩展到具有满足某些属性的求平均操作的通用度量空间。

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