Two-Dimensional Hardy–Littlewood Theorem for Functions with General Monotone Fourier Coefficients

IF 1.2 3区 数学 Q2 MATHEMATICS, APPLIED Journal of Fourier Analysis and Applications Pub Date : 2023-09-19 DOI:10.1007/s00041-023-10039-x
Kristina Oganesyan
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Abstract

Abstract We prove the Hardy–Littlewood theorem in two dimensions for functions whose Fourier coefficients obey general monotonicity conditions and, importantly, are not necessarily positive. The sharpness of the result is given by a counterexample, which shows that if one slightly extends the considered class of coefficients, the Hardy–Littlewood relation fails.

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一般单调傅里叶系数函数的二维Hardy-Littlewood定理
摘要在二维条件下证明了傅里叶系数服从一般单调性条件的函数的Hardy-Littlewood定理,重要的是,它不一定是正的。通过一个反例给出了结果的清晰性,该反例表明,如果稍微扩展所考虑的系数类别,Hardy-Littlewood关系将失效。
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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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