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Regularized Methods for the Split Feasibility Problem

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  • Yonghong Yao
  • Wu Jigang
  • Yeong-Cheng Liou

Abstract

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).

Suggested Citation

  • Yonghong Yao & Wu Jigang & Yeong-Cheng Liou, 2012. "Regularized Methods for the Split Feasibility Problem," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-13, February.
    • Handle: RePEc:hin:jnlaaa:140679
    DOI: 10.1155/2012/140679
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    Cited by:

    1. Li-Jun Zhu & Yonghong Yao, 2019. "An Iterative Approach to the Solutions of Proximal Split Feasibility Problems," Mathematics, MDPI, vol. 7(2), pages 1-9, February.
    2. Yan-Juan He & Li-Jun Zhu & Nan-Nan Tan, 2021. "An Improved Alternating CQ Algorithm for Solving Split Equality Problems," Mathematics, MDPI, vol. 9(24), pages 1-10, December.

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