Continuous Wavelet Transform of Schwartz Tempered Distributions in S0(Rn)

Jagdish Narayan Pandey; Jay Singh Maurya; Santosh Kumar Upadhyay; Hari Mohan Srivastava

dc.contributor.author	Jagdish Narayan Pandey
dc.contributor.author	Jay Singh Maurya
dc.contributor.author	Santosh Kumar Upadhyay
dc.contributor.author	Hari Mohan Srivastava
dc.date.accessioned	2019-07-16T07:01:37Z
dc.date.available	2019-07-16T07:01:37Z
dc.date.issued	2019-02-15
dc.identifier.issn	20738994
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/322
dc.description.abstract	In this paper, we define a continuous wavelet transform of a Schwartz tempered distribution f 2 S0 (Rn) with wavelet kernel y 2 S(Rn) and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of S0 (Rn). 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.	en_US
dc.language.iso	en	en_US
dc.publisher	MDPI AG	en_US
dc.subject	function spaces and their duals; distributions; tempered distributions; Schwartz testing function space; generalized functions; distribution space; wavelet transform of generalized functions; Fourier transform	en_US
dc.title	Continuous Wavelet Transform of Schwartz Tempered Distributions in S0(Rn)	en_US
dc.type	Article	en_US