Wavelet Based Numerical Scheme for Differential Equations (original) (raw)
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International Journal of Applied Mathematics and Mechanics, 2012
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Differential Equations and Dynamical Systems, 2017
A wavelet based rationalized method is presented for the numerical solution of differential, integral and integro-differential equations. Rationalized Haar functions are used to estimate the solution. Their fundamental properties are discussed. A rigorous convergence analysis is presented. The operational matrix of the product of two rationalized Haar functions is used to reduce the dynamical system to an algebraic system. A variety of model problems are taken into account so as to test the efficiency of the proposed method. The result so obtained are compared with the available exact solutions. In addition, proposed scheme is compared with some state of the art existing methods. It is found that the Haar wavelet operational matrix is the fastest. Moreover, the results obtained are mathematically simple and the desired accuracy of the solution is obtained using small number of grid points. The main advantages of the wavelet method are its simplicity, fast transformation, possibility of implementation of fast algorithms and low computational cost with high accuracy.
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Natural and Applied Sciences International Journal (NASIJ)
An effective wavelet based scheme coupled with finite difference is used for the solution of two nonlinear time dependent problems namely: Burgers' and Boussinesq equations. These equations have wide-spread application in many fields such as viscous medium, turbulence , uid dynamics, infiltration phenomena etc. The proposed scheme convert the partial differential equations (PDE) to system of algebraic equations. The obtained system can be solved easily. In this paper convergence of the scheme is also discussed to show validity of the technique. Effectiveness of the scheme is shown with the help of test problems. Numerical results verify that the suggested scheme is more accurate, convenient, fast and require low computational cost.