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Generalized Gradient Methods for Solving Locally Lipschitz Feasibility Problems

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Generalized Gradient Methods for Solving Locally Lipschitz Feasibility Problems

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dc.contributor.author Butnariu, Dan en
dc.date.accessioned 2010-06-09T15:46:19Z en
dc.date.available 2010-06-09T15:46:19Z en
dc.date.issued 1990-12 en
dc.identifier.uri http://hdl.handle.net/10106/2447 en
dc.description.abstract In this paper we study the behavior of a class of iterative algorithms for solving feasibility problems, that is finite systems of inequalities [see pdf for notation], where each [see pdf for notation] is a locally Lipschitz functional on a Hilbert space X. We show that, under quite mild conditions, the algorithms studied in this note, if converge, then they approximate a solution of the feasibility given problem, provided that the feasibility problem is consistent. We prove several convergence criteria showing that, when the envelope of the functionals [see pdf for notation], is sufficiently "regular", then the algorithms converge. The class of algorithms studied in this note contains, as special cases, many of the subgradient and projection methods of solving convex feasibility problems discussed in the literature. en
dc.language.iso en_US en
dc.publisher University of Texas at Arlington en
dc.relation.ispartofseries Technical Report;277 en
dc.subject Feasibility problems en
dc.subject Iterative algorithms en
dc.subject Lipschitz functional en
dc.subject Algorithms en
dc.subject Convex feasibility problems en
dc.subject.lcsh Mathematics Research en
dc.title Generalized Gradient Methods for Solving Locally Lipschitz Feasibility Problems en
dc.type Technical Report en
dc.publisher.department Department of Mathematics en

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