2012
DOI: 10.1155/2012/876069
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A Modified Halpern's Iterative Scheme for Solving Split Feasibility Problems

Abstract: The purpose of this paper is to introduce and study a modified Halpern's iterative scheme for solving the split feasibility problem SFP in the setting of infinite-dimensional Hilbert spaces. Under suitable conditions a strong convergence theorem is established. The main result presented in this paper improves and extends some recent results done by Xu Iterative methods for the split feasibility problem in infinite-dimensional Hilbert space, Inverse Problem 26 2010 105018 and some others.

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Cited by 7 publications
(8 citation statements)
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“…Osilike and Isiogugu [11] introduced a class of nonspreading type mappings which is more general than that of the mappings studied in [12] in Hilbert spaces and proved some weak and strong convergence theorems in real Hilbert spaces. Recently, the split feasibility problem also was considered in the work by Deepho and Kumam [13,14] and Sunthrayuth et al [15], and some weak and strong convergence theorems are proved in real Hilbert spaces.…”
Section: Abstract and Applied Analysismentioning
confidence: 99%
“…Osilike and Isiogugu [11] introduced a class of nonspreading type mappings which is more general than that of the mappings studied in [12] in Hilbert spaces and proved some weak and strong convergence theorems in real Hilbert spaces. Recently, the split feasibility problem also was considered in the work by Deepho and Kumam [13,14] and Sunthrayuth et al [15], and some weak and strong convergence theorems are proved in real Hilbert spaces.…”
Section: Abstract and Applied Analysismentioning
confidence: 99%
“…Hence, our algorithm (17) appears more efficient and implementable than the algorithm of Wang [25]. and Kumam [7] are dispensed with in our result even in higher Banach spaces than Hilbert where the result of Deepho and Kumam [7] was proved.…”
Section: Remark 43mentioning
confidence: 61%
“…2. In implementing the algorithm (7), one has to calculate, at each iteration, the Bregman projection onto the intersection of two half spaces but in this our iterative algorithm (17), one does not have to calculate, at each iteration, the Bregman projection onto the intersection of two half spaces. Hence, our algorithm (17) appears more efficient and implementable than the algorithm of Wang [25].…”
Section: Remark 43mentioning
confidence: 99%
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“…Recently, it has been found that the S F P can also be used to study of intensity‐modulated radiation therapy, see Censor et al,() and it has been studied by many researchers. ()…”
Section: Introductionmentioning
confidence: 99%