求解大规模绝对值方程 Ax - |x| = b 的非精确牛顿式方法

Pub Date : 2023-08-31 DOI:10.21136/AM.2023.0171-22
Jingyong Tang
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引用次数: 0

摘要

牛顿型方法已成功应用于求解绝对值方程 Ax - |x| = b(用 AVE 表示)。这类方法通常在每次迭代中精确求解线性方程组。然而,对于大规模的 AVE,精确求解相应的系统可能代价高昂。本文提出了一种求解 AVE 的非精确牛顿型方法。在每次迭代中,所提出的方法只能近似地求解相应的系统。此外,它采用了一种新的线搜索技术,定义明确且易于实现。我们证明,在区间矩阵 [A - I, A + I] 规则的条件下,所提出的方法具有全局和局部超线性收敛性。这一条件比某些牛顿型方法所使用的条件要弱得多。数值结果表明,我们的方法在求解大规模 AVE 时具有相当好的实用效率。
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Inexact Newton-type method for solving large-scale absolute value equation Ax − |x| = b

Newton-type methods have been successfully applied to solve the absolute value equation Ax − |x| = b (denoted by AVE). This class of methods usually solves a system of linear equations exactly in each iteration. However, for large-scale AVEs, solving the corresponding system exactly may be expensive. In this paper, we propose an inexact Newton-type method for solving the AVE. In each iteration, the proposed method solves the corresponding system only approximately. Moreover, it adopts a new line search technique, which is well-defined and easy to implement. We prove that the proposed method has global and local superlinear convergence under the condition that the interval matrix [AI, A + I] is regular. This condition is much weaker than those used in some Newton-type methods. Numerical results show that our method has fairly good practical efficiency for solving large-scale AVEs.

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