NON-STRICTLY CONVEX MINIMIZATION OVER THE FIXED POINT SET OF AN ASYMPTOTICALLY SHRINKING NONEXPANSIVE MAPPING

Suppose that T is a nonexpansive mapping on a real Hilbert space satisfying for some R > 0. Suppose also that a mapping is κ-Lipschitzian over and paramonotone over . Then it is shown that a variation of the hybrid steepest descent method (Yamada, Ogura, Yamashita and Sakaniwa (1998), Deutsch and...

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Published inNumerical functional analysis and optimization Vol. 23; no. 1-2; pp. 113 - 137
Main Authors Ogura, Nobuhiko, Yamada, Isao
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 05.01.2002
Subjects
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ISSN0163-0563
1532-2467
DOI10.1081/NFA-120003674

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Abstract Suppose that T is a nonexpansive mapping on a real Hilbert space satisfying for some R > 0. Suppose also that a mapping is κ-Lipschitzian over and paramonotone over . Then it is shown that a variation of the hybrid steepest descent method (Yamada, Ogura, Yamashita and Sakaniwa (1998), Deutsch and Yamada (1998) and Yamada (1999-2001)): generates a sequence (u n ) satisfying , when is finite dimensional, where for all is the solution set of the variational inequality problem . This result relaxes the condition on and (λ n ) of the hybrid steepest descent method (Yamada (2001)), and makes the method applicable to the significantly wider class of convexly constrained inverse problems as well as the non-strictly convex minimization over the fixed point set of asymptotically shrinking nonexpansive mapping.
AbstractList Suppose that T is a nonexpansive mapping on a real Hilbert space satisfying for some R > 0. Suppose also that a mapping is κ-Lipschitzian over and paramonotone over . Then it is shown that a variation of the hybrid steepest descent method (Yamada, Ogura, Yamashita and Sakaniwa (1998), Deutsch and Yamada (1998) and Yamada (1999-2001)): generates a sequence (u n ) satisfying , when is finite dimensional, where for all is the solution set of the variational inequality problem . This result relaxes the condition on and (λ n ) of the hybrid steepest descent method (Yamada (2001)), and makes the method applicable to the significantly wider class of convexly constrained inverse problems as well as the non-strictly convex minimization over the fixed point set of asymptotically shrinking nonexpansive mapping.
Author Ogura, Nobuhiko
Yamada, Isao
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  organization: Department of Communications and Integrated Systems , Tokyo Institute of Technology
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Snippet Suppose that T is a nonexpansive mapping on a real Hilbert space satisfying for some R > 0. Suppose also that a mapping is κ-Lipschitzian over and paramonotone...
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SubjectTerms 2000 Mathematics Subject Classification
Convex optimization
Convex projection
Fixed point theorem
Generalized convex feasible set
Inverse problem
Monotone operator
Nonexpansive mapping
Steepest descent method
Variational inequality problem
Title NON-STRICTLY CONVEX MINIMIZATION OVER THE FIXED POINT SET OF AN ASYMPTOTICALLY SHRINKING NONEXPANSIVE MAPPING
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