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Convergence analysis of the over-relaxed proximal point algorithms with errors for generalized nonlinear random operator equations

机译:广义非线性随机算子方程带误差的过度松弛近点算法的收敛性分析

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摘要

The purpose of this paper is to introduce and study the over-relaxed proximal point algorithms with errors for generalized nonlinear random operator equations with H-maximal monotonicity framework. Further, by using the generalized proximal operator technique associated with the H-maximal monotone operators, we discuss the approximation solvability of generalized nonlinear random operator equations in Hilbert spaces and the convergence analysis of iterative sequences generated by the over-relaxed proximal point algorithms with errors under some suit conditions, which generalize and improve the the over-relaxed proximal point algorithms due to Verma [R.U. Verma, The over-relaxed proximal point algorithm based on H-maximal monotonicity design and applications, Computers and Mathematics with Applications 55 (2008) 2673-2679].
机译:本文的目的是介绍和研究具有H-极大单调性框架的广义非线性随机算子方程的带误差的过度松弛近点算法。此外,通过使用与H-极大单调算子相关的广义近邻算子技术,我们讨论了希尔伯特空间中广义非线性随机算子方程的逼近可解性以及过度松弛的近点算法产生的带有误差的迭代序列的收敛性分析。在某些合适的条件下,归纳和改进了Verma [RU Verma,基于H极大单调性的过松弛近端点算法设计和应用,《计算机与数学及其应用》 55(2008)2673-2679]。

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