Minimizing certain convex functions over the intersection of the fixed point sets of nonexpansive mappings

被引:0
|
作者
Deutsch, F
Yamada, I
机构
[1] Penn State Univ, Dept Math, University Pk, PA 16802 USA
[2] Tokyo Inst Technol, Dept Elect & Elect Engn, Meguro Ku, Tokyo 152, Japan
关键词
nonexpansive mapping; fixed point theorem; convex optimization; steepest descent method; quadratic function; convex projection; best approximation; convex feasibility problem; generalized convex feasible set;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Let T(i) (i = 1,2,...,N) be nonexpansive mappings on a Hilbert space H, and let Theta : H --> RU{infinity} be a function which has a uniformly strongly positive and uniformly bounded second (Frechet) derivative over the convex huh of T(i)(H) for some i. We first prove that Theta has a unique minimum over the intersection of the fixed point sets of all the T(i)'s at some point u*. Then a cyclic hybrid steepest descent algorithm is proposed and we prove that it converges to u*. This generalizes some recent results of Wittmann (1992), Combettes (1995), Bauschke (1996), and Yamada, Ogura, Yamashita, and Sakaniwa (1997). In particular, the minimization of Theta over the intersection boolean AND(1)(N)C(i) of closed convex sets C(i) can be handled by taking T(i) to be the metric projection P(Ci) onto C(i). We also propose a modification of our algorithm to handle the inconsistent case (i.e., when boolean AND(1)(N)C(i) is empty) as well.
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页码:33 / 56
页数:24
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