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Approximate Schur-Block ILU Preconditioners for Regularized Solution of Discrete Ill-Posed Problems

机译:近似的孤独池ilu预处理器,用于定期解除问题的正规解

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High order iterative methods with a recurrence formula for approximate matrix inversion are proposed such that the matrix multiplications and additions in the calculation of matrix polynomials for the hyperpower methods of orders of convergence p = 4 k + 3 , where k ≥ 1 is integer, are reduced through factorizations and nested loops in which the iterations are defined using a recurrence formula. Therefore, the computational cost is lowered from κ = 4 k + 3 to κ = k + 4 matrix multiplications per step. An algorithm is proposed to obtain regularized solution of ill-posed discrete problems with noisy data by constructing approximate Schur-Block Incomplete LU (Schur-BILU) preconditioner and by preconditioning the one step stationary iterative method. From the proposed methods of approximate matrix inversion, the methods of orders p = 7,11,15,19 are applied for approximating the Schur complement matrices. This algorithm is applied to solve two problems of Fredholm integral equation of first kind. The first example is the harmonic continuation problem and the second example is Phillip’s problem. Furthermore, experimental study on some nonsymmetric linear systems of coefficient matrices with strong indefinite symmetric components from Harwell-Boeing collection is also given. Numerical analysis for the regularized solutions of the considered problems is given and numerical comparisons with methods from the literature are provided through tables and figures.
机译:提出了具有近似矩阵反演的复发公式的高阶迭代方法,使得矩阵多项式在收敛性阶数的超高力方法计算的矩阵多项式中的添加,其中k≥1是整数,是通过构思和嵌套环减少,其中使用复发公式定义迭代。因此,计算成本从κ= 4 k + 3到κ= k + 4矩阵乘法的计算成本降低。提出了一种算法,通过构建近似孤傲的侦察器和预处理静止迭代方法来获得噪声数据的正则化离散问题的正则化解。从近似矩阵反转的所提出的方法,施加订单P = 7,11,15,19的方法,用于近似SCHUR补充矩阵。应用该算法来解决第一类Fredholm积分方程的两个问题。第一个例子是谐波延续问题,第二个例子是菲利普的问题。此外,还给出了来自Harwell Boeing集合具有强不定对称组分的跨越系数矩阵的一些非对称线性系统的实验研究。给出了所考虑的问题的正则化解决方案的数值分析,并通过表格和数字提供了与文献方法的数值比较。

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