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
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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.