A regularized continuous method of gradient projection for minimization problems with inaccurate initial data

A. Nedich

A regularized continuous method of gradient projection for minimization problems with inaccurate initial data

Research output: Contribution to journal › Article › peer-review

Abstract

A continuous method of regularization is proposed for minimization problems with inaccurately given target function and set. The method is based on the gradient projection method. The sufficient conditions of the method's convergence are given, the regularizing operator is synthesized, the method's convergence rates are estimated.

Original language	English (US)
Pages (from-to)	3-10
Number of pages	8
Journal	Vestnik Moskovskogo Universiteta. Ser. 15 Vychislitel'naya Matematika i Kibernetika
Issue number	1
State	Published - Mar 1 1994
Externally published	Yes

ASJC Scopus subject areas

Software
Hardware and Architecture
Applied Mathematics

Cite this

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title = "A regularized continuous method of gradient projection for minimization problems with inaccurate initial data",

abstract = "A continuous method of regularization is proposed for minimization problems with inaccurately given target function and set. The method is based on the gradient projection method. The sufficient conditions of the method's convergence are given, the regularizing operator is synthesized, the method's convergence rates are estimated.",

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A regularized continuous method of gradient projection for minimization problems with inaccurate initial data

Abstract

ASJC Scopus subject areas

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