Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13508
 Title: Numerical methods for differential equations with distributional derivatives Authors: LI YONGFENG Keywords: Discrete singularity convolution(DSC), sampling theory, regularized Shannon kernel(RSK), delta distribution, sequence of delta type, convergence rate. Issue Date: 29-Oct-2003 Source: LI YONGFENG (2003-10-29). Numerical methods for differential equations with distributional derivatives. ScholarBank@NUS Repository. Abstract: A recently developed numerical method, the discrete singular convolution (DSC) method, for solving high order differential equations with distributional derivatives is presented in the different framework of distribution theory and sampling theory, respectively. In order to use this method to solve a class of differential equations with the delta distribution and its distributional derivatives, the classical approximations to the delta distribution and their convergence rates in Sobolev space $H^\alpha$ of negative order $\alpha$ are studied in details. As an example, the model of Euler-Bernoulli beam with jump discontinuities is used to test the efficiency of some delta sequences and the DSC method. URI: http://scholarbank.nus.edu.sg/handle/10635/13508 Appears in Collections: Master's Theses (Open)

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