IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v271y2015icp832-837.html
   My bibliography  Save this article

On choices of iteration parameter in HSS method

Author

Listed:
  • Chen, Fang

Abstract

The HSS iteration method is effective to solve non-Hermitian positive definite linear systems, but the choice of its optimal parameter is a difficult and challenging problem in theoretical analysis and practical computations. In this paper, we obtain an accurate estimate to the optimal parameter of the HSS iteration method by adopting a reasonable and simple optimization principle. Numerical experiments show that this principle is feasible to produce an accurate estimate to the optimal parameter of the HSS iteration method.

Suggested Citation

  • Chen, Fang, 2015. "On choices of iteration parameter in HSS method," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 832-837.
    • Handle: RePEc:eee:apmaco:v:271:y:2015:i:c:p:832-837
    DOI: 10.1016/j.amc.2015.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315012217
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2015.09.003?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Ling, Si-Tao & Liu, Qing-Bing, 2017. "New local generalized shift-splitting preconditioners for saddle point problems," Applied Mathematics and Computation, Elsevier, vol. 302(C), pages 58-67.
    2. Huang, Zheng-Ge & Wang, Li-Gong & Xu, Zhong & Cui, Jing-Jing, 2017. "The generalized modified shift-splitting preconditioners for nonsymmetric saddle point problems," Applied Mathematics and Computation, Elsevier, vol. 299(C), pages 95-118.
    3. Kai Jiang & Jianghao Su & Juan Zhang, 2022. "A Data-Driven Parameter Prediction Method for HSS-Type Methods," Mathematics, MDPI, vol. 10(20), pages 1-24, October.
    4. Huang, Zheng-Ge & Wang, Li-Gong & Xu, Zhong & Cui, Jing-Jing, 2020. "An efficient preconditioned variant of the PSS preconditioner for generalized saddle point problems," Applied Mathematics and Computation, Elsevier, vol. 376(C).

    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:eee:apmaco:v:271:y:2015:i:c:p:832-837. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.