Convolutions with probability densities and applications to PDEs

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dc.contributor.authorGal, Sorin
dc.date.accessioned2022-06-13T14:40:23Z
dc.date.available2022-06-13T14:40:23Z
dc.date.issued2017-09-13
dc.description.abstractIn this article we introduce several new convolution operators, generated by some known probability densities. By using the inverse Fourier transform and taking inverse steps (in the analogues of the classical procedures used for example in the heat or Laplace equations), we deduce the initial and final value problems satisfied by the new convolution integrals.
dc.description.departmentMathematics
dc.formatText
dc.format.extent9 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationGal, S. G. (2017). Convolutions with probability densities and applications to PDEs. Electronic Journal of Differential Equations, 2017(216), pp. 1-9.
dc.identifier.issn1072-6691
dc.identifier.urihttps://hdl.handle.net/10877/15910
dc.language.isoen
dc.publisherTexas State University, Department of Mathematics
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElectronic Journal of Differential Equations, 2017, San Marcos, Texas: Texas State University and University of North Texas.
dc.subjectProbability density
dc.subjectConvolution integral
dc.subjectFourier transform
dc.subjectInitial value problem
dc.subjectFinal value problem
dc.titleConvolutions with probability densities and applications to PDEs
dc.typeArticle

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