Self-adaptive algorithms for proximal split feasibility problems and strong convergence analysis

The purpose of the paper is to study the proximal split feasibility problems. For solving the problems, we present new self-adaptive algorithms with the regularization technique. By using these algorithms, we give some strong convergence theorems for the proximal split feasibility problems.

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Bibliographische Detailangaben
Veröffentlicht in:	Fixed point theory and algorithms for sciences and engineering 2015-11, Vol.2015 (1), p.1-13, Article 205
Hauptverfasser:	Yao, Yonghong, Yao, Zhangsong, Abdou, Afrah AN, Cho, Yeol Je
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Applications of Mathematics Convergence Differential Geometry Feasibility Mathematical and Computational Biology Mathematics Mathematics and Statistics New Challenges and Trends in Fixed Point Theory and Its Applications Regularization Theorems Topology
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Beschreibung
Zusammenfassung:	The purpose of the paper is to study the proximal split feasibility problems. For solving the problems, we present new self-adaptive algorithms with the regularization technique. By using these algorithms, we give some strong convergence theorems for the proximal split feasibility problems.
ISSN:	1687-1812 1687-1812 2730-5422
DOI:	10.1186/s13663-015-0462-7