2019
DOI: 10.1016/j.acha.2019.04.001
|View full text |Cite
|
Sign up to set email alerts
|

A continuous spherical wavelet transform for C(Sn)

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
7
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(7 citation statements)
references
References 18 publications
(29 reference statements)
0
7
0
Order By: Relevance
“…Theories of continuous spherical wavelets have been developed in the last decades, simultaneously to theories of wavelets over Euclidean space. Iglewska-Nowak has shown in [23,Section 5] that there exist only two essentially different continuous wavelet transforms for spherical signals, namely that based on group theory [2,3] and that derived from approximate identities [10,12,22,23]. In the present paper we show that the latter one can be efficiently applied to solving partial differential equations on the sphere.…”
Section: Introductionmentioning
confidence: 72%
See 4 more Smart Citations
“…Theories of continuous spherical wavelets have been developed in the last decades, simultaneously to theories of wavelets over Euclidean space. Iglewska-Nowak has shown in [23,Section 5] that there exist only two essentially different continuous wavelet transforms for spherical signals, namely that based on group theory [2,3] and that derived from approximate identities [10,12,22,23]. In the present paper we show that the latter one can be efficiently applied to solving partial differential equations on the sphere.…”
Section: Introductionmentioning
confidence: 72%
“…In the first case, the constraints on a function to be a wavelet are quite restrictive, but the inverse transform is given directly by an integral. This is the more popular version of the wavelet transform, developed starting from the 1990s by Freeden et al [12,13,14] and Bernstein et al [5,10], as well as by Iglewska-Nowak in the recent years [22,23,24,25].…”
Section: Two Wavelet Transformsmentioning
confidence: 99%
See 3 more Smart Citations