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Iterative algorithms for the multiple-sets split feasibility problem in Hilbert spaces

机译:Hilbert空间中多集分割可行性问题的迭代算法

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摘要

In this paper, for the multiple-sets split feasibility problem, that is to find a point closest to a family of closed convex subsets in one space such that its image under a linear bounded mapping will be closest to another family of closed convex subsets in the image space, we study several iterative methods for finding a solution, which solves a certain variational inequality. We show that particular cases of our algorithms are some improvements for existing ones in literature. We also give two numerical examples for illustrating our algorithms.
机译:在本文中,对于多套的分割可行性问题,即找到一个空间中最接近闭合凸子集的族的点,使得其在线性有界映射下的图像将最接近另一个闭合凸子子集 图像空间,我们研究了几种用于查找解决方案的迭代方法,该方法解决了某种变分不等式。 我们展示了我们算法的特定情况是对文学中现有的一些改进。 我们还给出了两个数字示例,用于说明我们的算法。

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