局部紧密阿贝尔群无拓扑同构于二维环的子群的海德定理

IF 1.2 3区 数学 Q2 MATHEMATICS, APPLIED
Gennadiy Feldman
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引用次数: 0

摘要

我们证明了著名的海德(Heyde)定理关于实线上高斯分布特征的以下群类似定理。设 X 是第二可数局部紧密阿贝尔群,其中不包含拓扑上与 2 维环面同构的子群。让 G 是 X 的子群,由 X 的所有阶为 2 的元素产生,让 \(\alpha \) 是群 X 的拓扑自变,使得 \(\textrm{Ker}(I+\alpha )=\{0\}\).让 \(\xi _1\) 和 \(\xi _2\) 是值在 X 中的独立随机变量,并且分布 \(\mu _1\) 和 \(\mu _2\) 具有非消失的特征函数。如果给定 \(L_1 = \xi _1 + \xi _2\) 的线性形式 \(L_2 = \xi _1 + \alpha \xi _2\) 的条件分布是对称的,那么 \(\mu _j\) 是 X 上的高斯分布和 G 中支持的分布的卷积。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heyde Theorem for Locally Compact Abelian Groups Containing No Subgroups Topologically Isomorphic to the 2-Dimensional Torus

We prove the following group analogue of the well-known Heyde theorem on a characterization of the Gaussian distribution on the real line. Let X be a second countable locally compact Abelian group containing no subgroups topologically isomorphic to the 2-dimensional torus. Let G be the subgroup of X generated by all elements of X of order 2 and let \(\alpha \) be a topological automorphism of the group X such that \(\textrm{Ker}(I+\alpha )=\{0\}\). Let \(\xi _1\) and \(\xi _2\) be independent random variables with values in X and distributions \(\mu _1\) and \(\mu _2\) with nonvanishing characteristic functions. If the conditional distribution of the linear form \(L_2 = \xi _1 + \alpha \xi _2\) given \(L_1 = \xi _1 + \xi _2\) is symmetric, then \(\mu _j\) are convolutions of Gaussian distributions on X and distributions supported in G. We also prove that this theorem is false if X is the 2-dimensional torus.

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来源期刊
CiteScore
2.10
自引率
16.70%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The Journal of Fourier Analysis and Applications will publish results in Fourier analysis, as well as applicable mathematics having a significant Fourier analytic component. Appropriate manuscripts at the highest research level will be accepted for publication. Because of the extensive, intricate, and fundamental relationship between Fourier analysis and so many other subjects, selected and readable surveys will also be published. These surveys will include historical articles, research tutorials, and expositions of specific topics. TheJournal of Fourier Analysis and Applications will provide a perspective and means for centralizing and disseminating new information from the vantage point of Fourier analysis. The breadth of Fourier analysis and diversity of its applicability require that each paper should contain a clear and motivated introduction, which is accessible to all of our readers. Areas of applications include the following: antenna theory * crystallography * fast algorithms * Gabor theory and applications * image processing * number theory * optics * partial differential equations * prediction theory * radar applications * sampling theory * spectral estimation * speech processing * stochastic processes * time-frequency analysis * time series * tomography * turbulence * uncertainty principles * wavelet theory and applications
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