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首页> 外文期刊>Journal of visual communication & image representation >A multiscale Galerkin method for second-order boundary value problems of Fredholm integro-differential equation Ⅱ: Efficient algorithm for the discrete linear system
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A multiscale Galerkin method for second-order boundary value problems of Fredholm integro-differential equation Ⅱ: Efficient algorithm for the discrete linear system

机译:Fredholm积分微分方程二阶边值问题的多尺度Galerkin方法Ⅱ:离散线性系统的高效算法

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A multiscale Galerkin method (MGM) was proposed recently by the same authors in order to solve second-order boundary value problems of Fredholm integro-differential equation. Although, the numerical solution of MGM is always stable because of the multiscale bases properties, obligatory of considerable computational cost and huge memory for achieving great approximation accuracy, are the main draw backs. To overcome MGM problems, in this paper, a new multilevel augmentation method (MAM) in order to solve discrete linear system is proposed. Applying the special matrix splitting techniques, approximate solution is obtained by (1) solving a linear system only at an initial lower level; (2) compensating the error by directly computing the product of matrices and vectors at the higher level without any iterations. Theoretical and experimental results approve that MAM and MGM have similar and optimum convergence orders, though MAM is more efficient than MGM. (C) 2018 Published by Elsevier Inc.
机译:同一作者最近提出了一种多尺度Galerkin方法(MGM),以解决Fredholm积分微分方程的二阶边值问题。尽管由于多尺度基数特性,MGM的数值解始终是稳定的,但主要缺点是必须要有大量的计算成本和巨大的内存才能获得较高的逼近精度。为了解决MGM问题,本文提出了一种新的多级增强方法(MAM),用于求解离散线性系统。应用特殊的矩阵分裂技术,可以通过以下方法获得近似解:(1)仅在初始较低水平上求解线性系统; (2)通过直接计算更高级别的矩阵和向量的乘积来补偿误差,而无需进行任何迭代。理论和实验结果都证明,尽管MAM比MGM更有效,但MAM和MGM具有相似的最佳收敛阶数。 (C)2018由Elsevier Inc.发布

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