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arXiv math/9406212math.PRmath.FA
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测度的集中与积空间中的等周不等式

Concentration of Measure and Isoperimetric Inequalities in Product Spaces

Michel Talagrand

摘要:

测度的集中性前提条件粗略地说明,如果概率空间的乘积$Ω^N$中的集合$A$具有至少一半的测度,则$Ω^N$的“大多数”点“接近”$A$。我们对这一现象进行了系统的探索。“大多数”一词的含义是严格的等周型不等式,约束的措施,例外集。作品“接近”的意义主要有三种定义,每一种都产生了相关但不同的不平等。所有的不等式都是通过一个共同的证明方案来证明的。值得注意的是,这种简单的方法不仅产生定性的最佳结果,但在许多情况下,捕获接近最佳的数值常数。大量的应用,特别是在渗流,几何概率,概率在巴拿赫空间,以证明在具体情况下的应用范围非常广泛的抽象工具。

英文摘要:

The concentration of measure prenomenon roughly states that, if a set $A$ in a product $Ω^N$ of probability spaces has measure at least one half, ``most'' of the points of $Ω^N$ are ``close'' to $A$. We proceed to a systematic exploration of this phenomenon. The meaning of the word ``most'' is made rigorous by isoperimetric-type inequalities that bound the measure of the exceptional sets. The meaning of the work ``close'' is defined in three main ways, each of them giving rise to related, but different inequalities. The inequalities are all proved through a common scheme of proof. Remarkably, this simple approach not only yields qualitatively optimal results, but, in many cases, captures near optimal numerical constants. A large number of applications are given, in particular in Percolation, Geometric Probability, Probability in Banach Spaces, to demonstrate in concrete situations the extremely wide range of application of the abstract tools.

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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