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A curvelet method for numerical solution of partial differential equations

机译:偏微分方程数值解的Curvelet方法

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This paper proposes a fast curvelet based finite difference method for numerical solutions of partial differential equations (PDEs). The method uses finite difference approximations for differential operators involved in the PDE5. After the approximation, the curvelet is used for the compression of the finite difference matrices and subsequently for computing the dyadic powers of these matrices required for solving the PDE in a fast and efficient manner. As a prerequisite, compression and reconstruction errors for the curvelet have been tested against different parameters. The developed method has been applied on five test problems of different nature. For each test problem the convergence of the method is examined. Moreover, to measure the performance of the proposed method the computational time taken by the proposed method is compared to that of the finite difference method. It is observed that the proposed method is computationally very efficient. (C) 2019 IMACS. Published by Elsevier B.V. All rights reserved.
机译:针对偏微分方程(PDE)的数值解,本文提出了一种基于快速Curvelet的有限差分方法。该方法对PDE5中涉及的微分算子使用有限差分近似。逼近之后,curvelet用于有限差分矩阵的压缩,随后用于快速有效地求解PDE所需的这些矩阵的二进幂。前提条件是,针对不同的参数测试了Curvelet的压缩和重构误差。所开发的方法已应用于五个不同性质的测试问题。对于每个测试问题,都检查了该方法的收敛性。此外,为了测量所提出方法的性能,将所提出方法所花费的计算时间与有限差分法所花费的时间进行了比较。可以看出,所提出的方法在计算上非常有效。 (C)2019年IMACS。由Elsevier B.V.发布。保留所有权利。

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