Super-Relaxed ()-Proximal Point Algorithms, Relaxed ()-Proximal Point Algorithms, Linear Convergence Analysis, and Nonlinear Variational Inclusions
نویسندگان
چکیده
منابع مشابه
Super-Relaxed (η)-Proximal Point Algorithms, Relaxed (η)-Proximal Point Algorithms, Linear Convergence Analysis, and Nonlinear Variational Inclusions
We glance at recent advances to the general theory of maximal set-valued monotone mappings and their role demonstrated to examine the convex programming and closely related field of nonlinear variational inequalities. We focus mostly on applications of the super-relaxed η proximal point algorithm to the context of solving a class of nonlinear variational inclusion problems, based on the notion ...
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First a general framework for a hybrid super-relaxed proximal point algorithm based on the notion of H-maximal monotonicity is introduced, and then the convergence analysis for solving a general class of nonlinear inclusion problems is explored. The framework developed in this communication is quite suitable to generalize first-order evolution equations based on the generalized nonlinear Yosida...
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Based on the notion of A−maximal relaxed accretiveness, the convergence analysis of the over-relaxed proximal point algorithm in the context of the approximating the solutions of a class of nonlinear variational inclusions is explored. Moreover, some results on the general firm nonexpansiveness are also investigated. The obtained results are general and application-oriented in nature.
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Based on the notion of A−maximal relaxed accretiveness, the convergence analysis of the over-relaxed proximal point algorithm in the context of the approximating the solutions of a class of nonlinear variational inclusions is explored. Moreover, some results on the general firm nonexpansiveness are also investigated. The obtained results are general and application-oriented in nature.
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ژورنال
عنوان ژورنال: Fixed Point Theory and Applications
سال: 2009
ISSN: 1687-1812
DOI: 10.1155/2009/957407