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Hybrid methods with regularization for minimization problems and asymptotically strict pseudocontractive mappings in the intermediate sense

机译:具有中化意义的最小化问题和渐近严格伪压缩映射的正则化混合方法

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摘要

In this paper we introduce an iterative algorithm for finding a common element of the fixed point set of an asymptotically strict pseudocontractive mapping S in the intermediate sense and the solution set of the minimization problem (MP) for a convex and continuously Frechet differentiable functional in Hilbert space. The iterative algorithm is based on several well-known methods including the extragradient method, CQ method, Mann-type iterative method and hybrid gradient projection algorithm with regularization. We obtain a strong convergence theorem for three sequences generated by our iterative algorithm. In addition, we also prove a new weak convergence theorem by a modified extragradient method with regularization for the MP and the mapping 5.
机译:在本文中,我们介绍了一种迭代算法,用于在中间意义上找到渐近严格伪压缩映射S的不动点集的公共元素以及Hilbert凸和连续Frechet可微泛函的最小化问题(MP)的解集空间。迭代算法基于几种众所周知的方法,包括超梯度方法,CQ方法,Mann型迭代方法和带正则化的混合梯度投影算法。对于迭代算法生成的三个序列,我们获得了一个强收敛定理。此外,我们还通过改进的超梯度方法对MP和映射5进行了正则化,证明了新的弱收敛定理。

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