IDEAS home Printed from https://ideas.repec.org/a/wly/jnlaaa/v2012y2012i1n432501.html

An Explicit Method for the Split Feasibility Problem with Self‐Adaptive Step Sizes

Author

Listed:
  • Youli Yu

Abstract

An explicit iterative method with self‐adaptive step‐sizes for solving the split feasibility problem is presented. Strong convergence theorem is provided.

Suggested Citation

  • Youli Yu, 2012. "An Explicit Method for the Split Feasibility Problem with Self‐Adaptive Step Sizes," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
  • Handle: RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:432501
    DOI: 10.1155/2012/432501
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2012/432501
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2012/432501?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yazheng Dang & Yan Gao & Yanli Han, 2012. "A Perturbed Projection Algorithm with Inertial Technique for Split Feasibility Problem," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
    2. Yazheng Dang & Yan Gao, 2012. "An Extrapolated Iterative Algorithm for Multiple-Set Split Feasibility Problem," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-12, May.
    3. Yazheng Dang & Yan Gao & Yanli Han, 2012. "A Perturbed Projection Algorithm with Inertial Technique for Split Feasibility Problem," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-10, May.
    4. Yazheng Dang & Yan Gao, 2012. "An Extrapolated Iterative Algorithm for Multiple‐Set Split Feasibility Problem," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhangsong Yao & Sun Young Cho & Shin Min Kang & Li-Jun Zhu, 2014. "A Regularized Algorithm for the Proximal Split Feasibility Problem," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yazheng Dang & Yan Gao, 2013. "Inertial Iteration for Split Common Fixed‐Point Problem for Quasi‐Nonexpansive Operators," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:432501. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/4058 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.