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Abstract and Applied Analysis
Volume 2012, Article ID 140679, 13 pages
Research Article

Regularized Methods for the Split Feasibility Problem

1Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, China
2School of Computer Science and Software, Tianjin Polytechnic University, Tianjin 300387, China
3Department of Information Management, Cheng Shiu University, Kaohsiung 833, Taiwan

Received 2 December 2011; Accepted 11 December 2011

Academic Editor: Khalida Inayat Noor

Copyright © 2012 Yonghong Yao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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).