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Self-Adaptive Algorithms for the Split Common Fixed Point Problem of the Demimetric Mappings

Self-Adaptive Algorithms for the Split Common Fixed Point Problem of the Demimetric Mappings
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摘要 The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper, we present new iterative algorithms for solving the split common fixed point problem of demimetric mappings in Hilbert spaces. Moreover, our algorithm does not need any prior information of the operator norm. Weak and strong convergence theorems are given under some mild assumptions. The results in this paper are the extension and improvement of the recent results in the literature. The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper, we present new iterative algorithms for solving the split common fixed point problem of demimetric mappings in Hilbert spaces. Moreover, our algorithm does not need any prior information of the operator norm. Weak and strong convergence theorems are given under some mild assumptions. The results in this paper are the extension and improvement of the recent results in the literature.
出处 《Journal of Applied Mathematics and Physics》 2019年第10期2187-2199,共13页 应用数学与应用物理(英文)
关键词 HILBERT Space Demimetric Mapping SPLIT Common Fixed Point PROBLEM SELF-ADAPTIVE Algorithm Hilbert Space Demimetric Mapping Split Common Fixed Point Problem Self-Adaptive Algorithm
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