Abstract

In this paper, a new and efficient approach for numerical approximation of second order linear partial differential-difference equations (PDDEs) with variable coefficients is introduced. Explicit formulae which express the two dimensional Jacobi expansion coefficients for the derivatives and moments of any differentiable function in terms of the original expansion coefficients of the function itself are given in the matrix form. The main importance of this scheme is that using this approach reduces solving the general linear PDDEs to solve a system of linear algebraic equations, wherein greatly simplify the problem. In addition, some experiments are given to demonstrate the validity and applicability of the method.

Highlights

  • partial differential-difference equations (PDDEs) arise in many branches of science and technology

  • Most physical phenomena of fluid dynamics, quantum mechanics, electricity, plasma physics, propagation of shallow water waves, and many other models are controlled within its domain of validity by PDDEs [5]

  • The essential behavior of most physical systems can be modeled by the second order linear PDDEs with variable coefficients

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Summary

Introduction

PDDEs arise in many branches of science and technology. For instance, in electromagnetic theory, physics, elasticity, fluid mechanics, heat transfer, acoustics, quantum mechanics, and so on [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]. The essential behavior of most physical systems can be modeled by the second order linear PDDEs with variable coefficients. The second order linear PDDEs with variable coefficients and their solutions play a major role in the branch of modern mathematics and arise frequently in many applied areas. We develop a new and efficient scheme (the general two dimensional shifted Jacobi matrix method) for numerical. Universal Journal of Applied Mathematics 1(2): 142-155, 2013 approximation of the second order linear PDDE (with the initial and boundary conditions which has a solution which is expressible as a known elementary function) in the following form. That we have computed the numerical results by Matlab (version 2013) programming

Preliminaries and notations
The one and two dimensional shifted Jacobi polynomials
The operational matrix
The method of solution
Approximations by Jacobi polynomials
The test experiments
Application of the method for the high order linear PDDEs
Conclution
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