Regularized Methods for the Split Feasibility Problem
Many applied problems such as image reconstructions and signal processing can be formulated as the split feasibility problem (SFP). Some algorithms have been introduced in the literature for solving the (SFP). In this paper, we will continue to consider the convergence analysis of the regularized me...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/140679 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Many applied problems such as image reconstructions and signal processing can
be formulated as the split feasibility problem (SFP). Some algorithms have been introduced in the literature for solving the (SFP). In this paper, we will continue to consider the convergence analysis of the regularized methods for the (SFP). Two
regularized methods are presented in the present paper. Under some different control
conditions, we prove that the suggested algorithms strongly converge to the minimum
norm solution of the (SFP). |
|---|---|
| ISSN: | 1085-3375 1687-0409 |