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New shrinking iterative methods for infinite families of monotone operators in a Banach space, computational experiments and applications

机译:Banach空间,计算实验和应用中单调算子无限家庭的新萎缩方法

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New shrinking iterative algorithms for approximating common zeros of two infinite families of maximal monotone operators in a real uniformly convex and uniformly smooth Banach space are designed. Two steps of multiple choices can be made in the new iterative algorithms, two groups of interactive containment sets $C_{n}$ and $Q_{n}$ are constructed and computational errors are considered, which are different from the previous ones. Strong convergence theorems are proved under mild assumptions and some new proof techniques can be found. Computational experiments for some special cases are conducted to show the effectiveness of the iterative algorithms and meanwhile some inequalities are proved to guarantee the strong convergence. Moreover, the applications of the abstract results on convex minimization problems and variational inequalities are exemplified.
机译:设计了新的次次迭代算法,用于在真正的均匀凸起和均匀平滑的Banach空间中设计两个最大单调算子的两个无限族家族的常见零。可以在新的迭代算法中进行多个选择的两步,两组交互式容器设置$ C_ {n} $和$ q_ {n} $是构造的,并且考虑计算错误,这与前一个算法不同。在温和的假设下证明了强大的收敛定理,可以找到一些新的校对技术。进行了一些特殊情况的计算实验,以显示迭代算法的有效性,同时证明了一些不等式以保证强烈的收敛性。此外,举例说明了摘要结果对凸起最小化问题和变分不等式的应用。

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