Continuous Wavelet Transform of Schwartz Tempered Distributions in S′ ( R n )

In this paper, we define a continuous wavelet transform of a Schwartz tempered distribution f ∈ S ′ ( R n ) with wavelet kernel ψ ∈ S ( R n ) and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of S ′ ( R n ) . It turns out that the wavelet transform...

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Vydáno v:Symmetry (Basel) Ročník 11; číslo 2; s. 235
Hlavní autoři: Pandey, Jagdish Narayan, Maurya, Jay Singh, Upadhyay, Santosh Kumar, Srivastava, Hari Mohan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.02.2019
Témata:
ISSN:2073-8994, 2073-8994
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Popis
Shrnutí:In this paper, we define a continuous wavelet transform of a Schwartz tempered distribution f ∈ S ′ ( R n ) with wavelet kernel ψ ∈ S ( R n ) and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of S ′ ( R n ) . It turns out that the wavelet transform of a constant distribution is zero and our wavelet inversion formula is not true for constant distribution, but it is true for a non-constant distribution which is not equal to the sum of a non-constant distribution with a non-zero constant distribution.
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ISSN:2073-8994
2073-8994
DOI:10.3390/sym11020235