The Fourier Transform on Rearrangement-Invariant Spaces

IF 1.2 3区 数学 Q2 MATHEMATICS, APPLIED
Ron Kerman, Rama Rawat, Rajesh K. Singh
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引用次数: 0

Abstract

Let \(\rho \) be a rearrangement-invariant (r.i.) norm on the set \(M({\mathbb {R}}^n)\) of Lebesgue-measurable functions on \({\mathbb {R}}^n\) such that the space \(L_{\rho }({\mathbb {R}}^n) = \left\{ f \in M({\mathbb {R}}^n): \rho (f) < \infty \right\} \) is an interpolation space between \(L_{2}({\mathbb {R}}^n)\) and \(L_{{\infty }}({\mathbb {R}}^n).\) The principal result of this paper asserts that given such a \(\rho ,\) the inequality

$$\begin{aligned} \rho ({\hat{f}}) \le C \sigma (f) \end{aligned}$$

holds for any r.i. norm \(\sigma \) on \( M({\mathbb {R}}^n)\) if and only if

$$\begin{aligned} {\bar{\rho }} \left( U f^{*} \right) \le C {\bar{\sigma }} (f^{*}). \end{aligned}$$

Here, \({\bar{\rho }}\) is the unique r.i. norm on \(M({\mathbb {R}}_+)\), \({\mathbb {R}}_+ = (0, \infty )\), satisfying \({\bar{\rho }}(f^{*})=\rho (f)\) and \(U f^{*} (t) = \int _{0}^{1/t} f^{*}\), in which \(f^{*}\) is the nonincreasing rearrangement of f on \(\mathbb {R_+}\). Further, in this case the smallest r.i. norm \(\sigma \) for which \(\rho ( {\hat{f}}) \le C \sigma (f)\) holds is given by

$$\begin{aligned} \sigma (f) = {\bar{\sigma }} (f^{*}) = {\bar{\rho }} \left( U f^{*}\right) , \end{aligned}$$

where, necessarily, \({\bar{\rho }} \left( \int _{0}^{1/t} \chi _{(0, a)} \right) = {\bar{\rho }} \left( \min \{1/t, \, a\} \right) < \infty \), for all \(a>0\). We further specialize and expand these results in the contexts of Orlicz and Lorentz Gamma spaces.

重排不变空间上的傅立叶变换
让 \(\rho \) 是集合 \(M({\mathbb {R}}^n) 上的一个重排不变(r.i.上 Lebesgue-measurable functions on \({\mathbb {R}}^n\) 的集合 \(M({\mathbb {R}}^n) 上的规范,使得空间 \(L_{\rho }({\mathbb {R}}^n) = \left\{ f \ in M({\mathbb {R}}^n):\rho (f) < \infty\right\}\是 L_{2}({\mathbb {R}}^n)\) 和 L_{{\infty }}({\mathbb {R}}^n) 之间的插值空间。本文的主要结果断言,给定这样一个 ( (rho ,\)不等式 $$\begin{aligned}\如果并且只有当 $$\begin{aligned} {bar\{rho }} 在 M({\mathbb {R}}^n)\) 上的任意 r.i. norm (\sigma)成立时,才会有 $$\rho ({\hat{f}}) \le C \sigma (f) \end{aligned}$$holds for any r.i. norm (\sigma)。\left( U f^{*} \right) \le C {\bar{sigma }}(f^{*}).\end{aligned}$$Here, \({\bar{\rho }}\) is the unique r.i.norm on \(M({\mathbb {R}}_+)\), \({\mathbb {R}}_+ = (0, \infty )\), satisfying \({\bar{rho }}(f^{*})=\rho (f)\) and\(U f^{*} (t) = \int _{0}^{1/t} f^{*}\)、其中 \(f^{*}\) 是 f 在 \(\mathbb {R_+}\) 上的非递增重排。此外,在这种情况下,\(\rho ( {\hat{f}}) \le C \sigma(f)\)成立的最小r.i. norm (r.i. norm)是由 $$\begin{aligned} 给出的。\sigma (f) = {\bar{\sigma }}(f^{*}) = {\bar{\rho }}\left( U f^{*}\right) , \end{aligned}$$其中,必然是({\bar{\rho }}\left( \int _{0}^{1/t}\chi _{(0, a)} \right) = {\bar{\rho }}\left( \min \{1/t, \, a} \right) < \infty \), for all \(a>0\).我们在奥尔利茨和洛伦兹伽马空间的背景下对这些结果做了进一步的特殊化和扩展。
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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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