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arXiv 1602.08712math.NAcs.NAmath.FAstat.ML
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关于混合光滑函数类的熵数

On the entropy numbers of the mixed smoothness function classes

University of South Carolina(南卡罗来纳大学);Steklov Institute of Mathematics(斯捷洛夫数学研究所)

V. Temlyakov

AI总结:

本文研究了具有混合光滑性的多变量函数类的熵数行为,提出基于非线性逼近的新方法,通过两步策略推导熵数上界,并利用体积估计法证明下界。

摘要:

本文研究了具有混合光滑性的多变量函数类的熵数行为。这个问题有长期历史,该领域仍存在一些根本性问题尚未解决。本文的主要目标是开发一种新的方法,用于证明熵数的上界。该方法基于非线性逼近的最新发展,特别是贪心逼近。该方法由以下两个步骤策略组成。第一步是获得相对于字典的最佳m项近似界。第二步是利用将熵数与最佳m项近似联系起来的一般不等式。对于下界,我们使用体积估计法,这是一种已知的强有力的证明熵数下界的常用方法。它已在许多先前论文中使用。

英文摘要:

Behavior of the entropy numbers of classes of multivariate functions with mixed smoothness is studied here. This problem has a long history and some fundamental problems in the area are still open. The main goal of this paper is to develop a new method of proving the upper bounds for the entropy numbers. This method is based on recent developments of nonlinear approximation, in particular, on greedy approximation. This method consists of the following two steps strategy. At the first step we obtain bounds of the best m-term approximations with respect to a dictionary. At the second step we use general inequalities relating the entropy numbers to the best m-term approximations. For the lower bounds we use the volume estimates method, which is a well known powerful method for proving the lower bounds for the entropy numbers. It was used in a number of previous papers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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