- Current Issue - Ahead of Print Articles - All Issues - Search - Open Access - Information for Authors - Downloads - Guideline - Regulations ㆍPaper Submission ㆍPaper Reviewing ㆍPublication and Distribution - Code of Ethics - For Authors ㆍOnline Submission ㆍMy Manuscript - For Reviewers - For Editors
 General framework for proximal point algorithms on $(A,\eta)$-maximal monotonicity for nonlinear variational inclusions Commun. Korean Math. Soc. 2011 Vol. 26, No. 4, 685-693 https://doi.org/10.4134/CKMS.2011.26.4.685Published online December 1, 2011 Ram U. Verma Seminole State College oF Florida Abstract : General framework for proximal point algorithms based on the notion of $(A,\eta)$-maximal monotonicity (also referred to as $(A,\eta)$-monotonicity in literature) is developed. Linear convergence analysis for this class of algorithms to the context of solving a general class of nonlinear variational inclusion problems is successfully achieved along with some results on the generalized resolvent corresponding to $(A,\eta)$-monotonicity. The obtained results generalize and unify a wide range of investigations readily available in literature. Keywords : variational inclusions, maximal monotone mapping, $(A,\eta)$-maximal monotone mapping, generalized resolvent operator MSC numbers : 49J40, 65B05 Downloads: Full-text PDF