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Cubo (Temuco)

versión On-line ISSN 0719-0646

Resumen

VERMA, Ram U. Linear Convergence Analysis for General Proximal Point Algorithms Involving (H,η)- Mo   notonicity Frameworks. Cubo [online]. 2011, vol.13, n.3, pp. 185-196. ISSN 0719-0646.  http://dx.doi.org/10.4067/S0719-06462011000300010.

General framework for the generalized proximal point algorithm, based on the notion of (H,r)- 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.

Palabras clave : General cocoerciveness; Variational inclusions; Maximal monotone mapping; (H,r) - monotone mapping; Generalized proximal point algorithm; Generalized resolvent operator..

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