Subgradient projection algorithms for convex feasibility problems in the presence of computational errors
- Autores: Alexander J. Zaslavski
- Localización: Journal of approximation theory, ISSN 0021-9045, Vol. 175, Nº 1, 2013, págs. 19-42
- Idioma: inglés
- DOI: 10.1016/j.jat.2013.07.012
- Enlaces
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Resumen
In the present paper we study convergence of subgradient projection algorithms for solving convex feasibility problems in a Hilbert space. Our goal is to obtain an approximate solution of the problem in the presence of computational errors. We show that our subgradient projection algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.
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