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- W4381886157 abstract "In this work, we aim at applying an appropriate kernelization approach to solve analytically the Wicktypestochastic Korteweg-de Vries (KdV) equation with variable coefficients. Per the benefit offormulating the problem in Hilbert space, we deliver a binary reproducing kernel Hilbert space (RKHS)structure to represent the solution of such problem in the suggested kernel Hilbert space. ImplyingHermite transform, white noise theory and proper binary reproducing kernel Hilbert spaces, we articulatewhite noise functional solutions for the Wick-type stochastic KdV equations. Representation of the exactsolution is given in some reproducing kernel space. The uniform convergence, of the approximatesolution together with its first derivative utilizing the suggested scheme, is investigated. The relevance ofour suggested approach is inspected partially on one of the most important spectral density study, namelythe cross power spectral density (CPSD) attests to the reliability of the scheme and highlighted the worthof the present work that can be applied on a wide class of nonlinear partial differential emerge innumerous physical modeling phenomena." @default.
- W4381886157 created "2023-06-25" @default.
- W4381886157 date "2023-03-01" @default.
- W4381886157 modified "2023-09-27" @default.
- W4381886157 doi "https://doi.org/10.22377/ajms.v7i1.473" @default.
- W4381886157 hasPublicationYear "2023" @default.
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