untitled
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<identifier>oai:HAL:hal-00776641v1</identifier>
<datestamp>2017-12-21</datestamp>
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<setSpec>subject:math</setSpec>
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<publisher>HAL CCSD</publisher>
<title lang=en>A Regularized Hybrid Steepest Descent Method for Variational Inclusions</title>
<creator>Moudafi, Abdellatif</creator>
<contributor>Centre de Recherche en Economie, Gestion, Modélisation et Informatique Appliquée (CEREGMIA) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>International audience</description>
<source>ISSN: 0163-0563</source>
<source>EISSN: 1532-2467</source>
<source>Numerical Functional Analysis and Optimization</source>
<publisher>Taylor & Francis</publisher>
<identifier>hal-00776641</identifier>
<identifier>https://hal.univ-antilles.fr/hal-00776641</identifier>
<source>https://hal.univ-antilles.fr/hal-00776641</source>
<source>Numerical Functional Analysis and Optimization, Taylor & Francis, 2012, 33 (1), pp.39-47. 〈10.1080/01630563.2011.619676〉</source>
<identifier>DOI : 10.1080/01630563.2011.619676</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1080/01630563.2011.619676</relation>
<language>en</language>
<subject lang=en>Convex constrained minimization</subject>
<subject lang=en>Hybrid steepest descent method</subject>
<subject lang=en>Monotone operator</subject>
<subject lang=en>Variational inequalities</subject>
<subject lang=en>Yosida approximate</subject>
<subject>[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>This article is concerned with a generalization of the hybrid steepest descent method from variational inequalities to the multivalued case. This will be reached by replacing the multivalued operator by its Yosida approximate, which is always Lipschitz continuous. It is worth mentioning that the hybrid steepest descent method is an algorithmic solution to variational inequality problems over the fixed point set of certain nonexpansive mappings and has remarkable applicability to the constrained nonlinear inverse problems like image recovery and MIMO communication systems</description>
<date>2012</date>
</dc>
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