论文信息 - Data Errors and an Error Estimation for Ill-Posed Problems

Data Errors and an Error Estimation for Ill-Posed Problems

In this paper we shall discuss the problem how to use a priori information for constructing regularizing algorithms and error estimation while solving ill-posed problems. We shall consider the following types of a priori information: (1) a compactness of a set of solutions; (2) a sourcewise representation of a solution with a compact operator.

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