Maximal Monotone Operators and the Proximal Point Algorithm in the Presence of Computational Errors
✍ Scribed by A. J. Zaslavski
- Publisher
- Springer
- Year
- 2011
- Tongue
- English
- Weight
- 441 KB
- Volume
- 150
- Category
- Article
- ISSN
- 0022-3239
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
In this paper we introduce general iterative methods for finding zeros of a maximal monotone operator in a Hilbert space which unify two previously studied iterative methods: relaxed proximal point algorithm [H.K. Xu, Iterative algorithms for nonlinear operators, J. London Math Soc. 66 (2002) 240-25
First the general framework for a generalized over-relaxed proximal point algorithm using the notion of H -maximal monotonicity (also referred to as H -monotonicity) is developed, and then the convergence analysis for this algorithm in the context of solving a general class of nonlinear inclusion pr
In this paper we give some conditions under which T q Ѩ f is maximal monotone Ž . in the Banach space X not necessarily reflexive , where T is a monotone operator from X into X \* and Ѩ f is the subdifferential of a proper lower semicontinuous Ä 4 convex function f, from X into ޒ j qϱ . We also gi