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A note about EC-(s, t)-weak tractability of multivariate approximation with analytic Korobov kernels

机译:关于使用解析Korobov核的多元逼近的EC-(s,t)-弱可延展性的注记

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This paper is devoted to discussing multivariate approximation problems with analytic Korobov kernels in the worst and average case settings. We consider algorithms that use finitely many evaluations of arbitrary continuous linear functionals. We investigate exponential convergence-(s, t)-weak tractability (EC-(s, t)-WT) under the absolute or normalized error criterion. We completely solve the problem by filling the remaining gaps left open on EC-(s, t)-WT. That is, we obtain necessary and sufficient conditions for EC-(s, t)-WT for 0 < min(s, t) < 1 and max(s, t) <= 1 in the worst case setting and for s, t > 0 except s = t = 1 in the average case setting. (C) 2019 Elsevier Inc. All rights reserved.
机译:本文致力于讨论在最坏情况和平均情况下使用解析Korobov核进行的多元逼近问题。我们考虑使用对任意连续线性函数进行有限多次求值的算法。我们研究在绝对或归一化误差准则下的指数收敛-(s,t)-弱可延展性(EC-(s,t)-WT)。我们通过填补EC-(s,t)-WT上剩余的空白来完全解决问题。也就是说,我们获得了EC-(s,t)-WT在最坏情况下的0 0,但在平均情况下,s = t = 1。 (C)2019 Elsevier Inc.保留所有权利。

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