2003
DOI: 10.1007/s00041-003-0003-3
|View full text |Cite
|
Sign up to set email alerts
|

Weighted Fourier Inequalities: New Proofs and Generalizations

Abstract: Fourier transform inequalities in weighted Lebesgue spaces are proved. The inequalities are generalizations of the Plancherel theorem, they are characterized in terms of uncertainty principle relations between pairs of weights, and they are put in the context of existing weighted Fourier transform inequalities. The proofs are new and relatively elementary, and they give rise to good and explicit constants controlling the continuity of the Fourier transform operator. The smaller the constant is, the more applic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

3
57
0
1

Year Published

2004
2004
2023
2023

Publication Types

Select...
5
4

Relationship

0
9

Authors

Journals

citations
Cited by 75 publications
(61 citation statements)
references
References 54 publications
3
57
0
1
Order By: Relevance
“…Relation (5) was proved in [20]; see also [12]. Thus, assuming a function to be monotone allows one to extend the range of γ as well as to reverse inequality (2) for p = q.…”
Section: Boas Conjectured Inmentioning
confidence: 95%
See 1 more Smart Citation
“…Relation (5) was proved in [20]; see also [12]. Thus, assuming a function to be monotone allows one to extend the range of γ as well as to reverse inequality (2) for p = q.…”
Section: Boas Conjectured Inmentioning
confidence: 95%
“…For n = 1, inequality (2) can be found in [5], [17], [18], [22]; for n ≥ 1, see [3], [5]. W. Beckner [2] found the sharp constant in (2) for p = q = 2 and used this to prove a logarithmic estimate for uncertainty.…”
Section: Introductionmentioning
confidence: 97%
“…3 can be obtained by the time-frequency analysis of trained data. This system determines the unknown weight coefficients with the forgetting factors method (Benedetto and Heinig 2003;Enns and Si 2002;Razavi and Araghinejad 2009).…”
Section: Learning Algorithm Of Wavelet Networkmentioning
confidence: 99%
“…[15,16,2] and the references therein). Let us mention that a weighted inequality for the Fourier transform was proved in [2] with the help of a result of Jodeit-Torchinsky [14] showing that an operator that is of type (1, ∞) and of type (2, 2) satisfies some rearrangement inequalities.…”
Section: Introductionmentioning
confidence: 99%