Linear convergence analysis for general proximal point algorithms involving (H, η) − monotonicity frameworks

dc.creator	Verma, Ram U.
dc.date	2011-10-01
dc.identifier	https://revistas.ufro.cl/ojs/index.php/cubo/article/view/1368
dc.identifier	10.4067/S0719-06462011000300010
dc.description	General framework for the generalized proximal point algorithm, based on the notion of (H, η) − monotonicity, is developed. The linear convergence analysis for the generalized proximal point algorithm to the context of solving a class of nonlinear variational inclusions is examined, The obtained results generalize and unify a wide range of problems to the context of achieving the linear convergence for proximal point algorithms.	en-US
dc.format	application/pdf
dc.language	eng
dc.publisher	Universidad de La Frontera. Temuco, Chile.	en-US
dc.relation	https://revistas.ufro.cl/ojs/index.php/cubo/article/view/1368/1222
dc.source	CUBO, A Mathematical Journal; Vol. 13 No. 3 (2011): CUBO, A Mathematical Journal; 185–196	en-US
dc.source	CUBO, A Mathematical Journal; Vol. 13 Núm. 3 (2011): CUBO, A Mathematical Journal; 185–196	es-ES
dc.source	0719-0646
dc.source	0716-7776
dc.subject	General cocoerciveness	en-US
dc.subject	Variational inclusions	en-US
dc.subject	Maximal monotone mapping	en-US
dc.subject	(H, η) − monotone mapping	en-US
dc.subject	Generalized proximal point algorithm	en-US
dc.subject	Generalized resolvent operator	en-US
dc.title	Linear convergence analysis for general proximal point algorithms involving (H, η) − monotonicity frameworks	en-US
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion