A Shrinking Projection Algorithm with Errors for Costerro Bounded Linear Mappings

Joseph Frank Gordon and Tepper L Gill

Journal of Mathematics, 2020, vol. 2020, 1-6

Abstract: The purpose of this paper is to introduce and analyze the shrinking projection algorithm with errors for a finite set of costerro bounded linear mappings in the setting of uniformly convex smooth Banach spaces. Here, under finite dimensional or compactness restriction or the error term being zero, the strong limit point of the sequence stated in the iterative scheme for these mappings in uniformly convex smooth Banach spaces was studied. This paper extends Ezearn and Prempeh’s result for nonexpansive mappings in real Hilbert spaces.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:7052349

DOI: 10.1155/2020/7052349

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