Strong Convergence of Tikhonov Regularization Method for Solving Ill-Posed Problems in Hilbert Spaces

Authors

  • Mohamed Soueycatt Tishreen University
  • Boushra Abbas Tishreen University
  • Layal Ali Tishreen University

Abstract

 

It is well-known that solving ill-posed problems numerically without using methods for regularization is difficult because any small change in the data implies to large and random errors in the solution. We restrict the attention to Tikhonov regularization method where the original ill-posed problem is replaced with finding solution to a stable convex optimization problem which is called a regularized solution.

This research aims to determine the convenient choice  of the regularization parameter in order to establish the strong convergence.

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Published

2019-03-11

How to Cite

1.
Soueycatt M, Abbas B, Ali L. Strong Convergence of Tikhonov Regularization Method for Solving Ill-Posed Problems in Hilbert Spaces. TUJ-BA [Internet]. 2019Mar.11 [cited 2024Apr.19];41(1). Available from: https://journal.tishreen.edu.sy/index.php/bassnc/article/view/8506

Issue

Vol. 41 No. 1 (2019): العلوم الأساسية

Section

Articles

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