Title :
Shrinking Projection Methods for Maximal Monotone Operators and Quasi-nonexpansive Mappings
Author :
Gao, Xinghui ; Ma, Lerong
Author_Institution :
Coll. of Math. & Comput. Sci., Yanan Univ., Yanan, China
Abstract :
In this paper, we consider a new shrinking projection method for finding common elements of the set of fixed points of a quasi-φ-nonexpansive mapping and the set of zero points of a maximal monotone operator. We establish a strong convergence theorem of common elements by using new analysis techniques in the setting of reflexive, strictly convex, smooth Banach spaces with the property (K). As an application, the problem of finding a minimizer of a convex function is considered.
Keywords :
Banach spaces; convergence; convex programming; convergence theorem; fixed points; maximal monotone operators; quasinonexpansive mappings; reflexive spaces; shrinking projection methods; smooth Banach spaces; strictly convex spaces; Artificial neural networks; Convergence; Convex functions; Mathematical model; Optical wavelength conversion; Social network services; System-on-a-chip; maximal monotone operator; quasi-f-nonexpansive mapping; shrinking projection methods; the property(K);
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-8785-1
DOI :
10.1109/CASoN.2010.63