{"title":"Continuous wavelet transform of Schwartz distributions in 𝒟′(ℝ𝑛), 𝑛 ≤ 1","authors":"J. Pandey","doi":"10.1515/anly-2021-0002","DOIUrl":null,"url":null,"abstract":"Abstract In this paper, we extend the continuous wavelet transform to Schwartz distributions in D ′ ( R n ) \\mathcal{D}^{\\prime}(\\mathbb{R}^{n}) , n ≥ 1 n\\geq 1 , and derive the corresponding wavelet inversion formula (valid modulo a constant distribution) interpreting convergence in the weak distributional sense. The kernel of our wavelet transform is an element ψ ( x ) \\psi(x) of D ( R n ) \\mathcal{D}(\\mathbb{R}^{n}) , n ≥ 1 n\\geq 1 , which, when integrated along each of the real axes X 1 , X 2 , X 3 , … , X n X_{1},X_{2},X_{3},\\ldots,X_{n} vanishes, but none of its moments ∫ R n ψ ( x ) x m d x \\int_{\\mathbb{R}^{n}}\\psi(x)x^{m}\\,dx is zero; here x m = x 1 m 1 x 2 m 2 … x n m n x^{m}=x_{1}^{{m_{1}}}\\,x_{2}^{{m_{2}}}\\ldots x_{n}^{{m_{n}}} , d x = d x 1 d x 2 … d x n dx=dx_{1}\\,dx_{2}\\ldots dx_{n} and m = ( m 1 , m 2 , … , m n ) m=(m_{1},m_{2},\\ldots,m_{n}) and each of m 1 , m 2 , … , m n m_{1},m_{2},\\ldots,m_{n} is at least 1. The set of such kernel will be denoted by D m ( R n ) \\mathcal{D}_{m}(\\mathbb{R}^{n}) . But the uniqueness theorem for our wavelet inversion formula is valid for the space D F ′ ( R n ) \\mathcal{D}_{F}^{\\prime}(\\mathbb{R}^{n}) obtained by filtering (deleting) (i) all non-zero constant distributions from the space D ′ ( R n ) \\mathcal{D}^{\\prime}(\\mathbb{R}^{n}) , (ii) all non-zero constants that appear with a distribution as a union as for example for x 1 2 + x 2 2 + ⋯ x n 2 1 + x 1 2 + x 2 2 + ⋯ x n 2 = 1 - 1 1 + x 1 2 + x 2 2 + ⋯ x n 2 \\frac{x_{1}^{2}+x_{2}^{2}+\\cdots x_{n}^{2}}{1+x_{1}^{2}+x_{2}^{2}+\\cdots x_{n}^{2}}=1-\\frac{1}{1+x_{1}^{2}+x_{2}^{2}+\\cdots x_{n}^{2}} , 1 is deleted and - 1 1 + x 1 2 + x 2 2 + ⋯ x n 2 \\frac{-1}{1+x_{1}^{2}+x_{2}^{2}+\\cdots x_{n}^{2}} is retained.","PeriodicalId":82310,"journal":{"name":"Philosophic research and analysis","volume":"21 1","pages":"133 - 139"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Philosophic research and analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/anly-2021-0002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract In this paper, we extend the continuous wavelet transform to Schwartz distributions in D ′ ( R n ) \mathcal{D}^{\prime}(\mathbb{R}^{n}) , n ≥ 1 n\geq 1 , and derive the corresponding wavelet inversion formula (valid modulo a constant distribution) interpreting convergence in the weak distributional sense. The kernel of our wavelet transform is an element ψ ( x ) \psi(x) of D ( R n ) \mathcal{D}(\mathbb{R}^{n}) , n ≥ 1 n\geq 1 , which, when integrated along each of the real axes X 1 , X 2 , X 3 , … , X n X_{1},X_{2},X_{3},\ldots,X_{n} vanishes, but none of its moments ∫ R n ψ ( x ) x m d x \int_{\mathbb{R}^{n}}\psi(x)x^{m}\,dx is zero; here x m = x 1 m 1 x 2 m 2 … x n m n x^{m}=x_{1}^{{m_{1}}}\,x_{2}^{{m_{2}}}\ldots x_{n}^{{m_{n}}} , d x = d x 1 d x 2 … d x n dx=dx_{1}\,dx_{2}\ldots dx_{n} and m = ( m 1 , m 2 , … , m n ) m=(m_{1},m_{2},\ldots,m_{n}) and each of m 1 , m 2 , … , m n m_{1},m_{2},\ldots,m_{n} is at least 1. The set of such kernel will be denoted by D m ( R n ) \mathcal{D}_{m}(\mathbb{R}^{n}) . But the uniqueness theorem for our wavelet inversion formula is valid for the space D F ′ ( R n ) \mathcal{D}_{F}^{\prime}(\mathbb{R}^{n}) obtained by filtering (deleting) (i) all non-zero constant distributions from the space D ′ ( R n ) \mathcal{D}^{\prime}(\mathbb{R}^{n}) , (ii) all non-zero constants that appear with a distribution as a union as for example for x 1 2 + x 2 2 + ⋯ x n 2 1 + x 1 2 + x 2 2 + ⋯ x n 2 = 1 - 1 1 + x 1 2 + x 2 2 + ⋯ x n 2 \frac{x_{1}^{2}+x_{2}^{2}+\cdots x_{n}^{2}}{1+x_{1}^{2}+x_{2}^{2}+\cdots x_{n}^{2}}=1-\frac{1}{1+x_{1}^{2}+x_{2}^{2}+\cdots x_{n}^{2}} , 1 is deleted and - 1 1 + x 1 2 + x 2 2 + ⋯ x n 2 \frac{-1}{1+x_{1}^{2}+x_{2}^{2}+\cdots x_{n}^{2}} is retained.