IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v273y2016icp525-534.html
   My bibliography  Save this article

Convergence studies on block iterative algorithms for image reconstruction

Author

Listed:
  • Guo, Xue-Ping

Abstract

The sequential block-iterative scheme based on Landweber’s method is a general iterative one for image reconstruction. In this paper, we give the finite termination convergence for this scheme, which provides an approach to choose relaxation coefficients. Furthermore, sufficient and necessary convergence conditions are also established for the sequential block-iterative scheme case.

Suggested Citation

  • Guo, Xue-Ping, 2016. "Convergence studies on block iterative algorithms for image reconstruction," Applied Mathematics and Computation, Elsevier, vol. 273(C), pages 525-534.
    • Handle: RePEc:eee:apmaco:v:273:y:2016:i:c:p:525-534
    DOI: 10.1016/j.amc.2015.10.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315013703
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2015.10.028?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.

    References listed on IDEAS

    as
    1. J. L. Goffin, 1980. "The Relaxation Method for Solving Systems of Linear Inequalities," Mathematics of Operations Research, INFORMS, vol. 5(3), pages 388-414, August.
    Full references (including those not matched with items on IDEAS)

    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. Epelman, Marina A., 1973-. & Freund, Robert Michael, 1997. "Condition number complexity of an elementary algorithm for resolving a conic linear system," Working papers WP 3942-97., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Amitabh Basu & Jesús A. De Loera & Mark Junod, 2014. "On Chubanov's Method for Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 336-350, May.
    3. Annabella Astorino & Manlio Gaudioso & Alberto Seeger, 2016. "Central axes and peripheral points in high dimensional directional datasets," Computational Optimization and Applications, Springer, vol. 65(2), pages 313-338, November.
    4. Alberto Seeger & José Vidal -Nuñez, 2017. "Measuring centrality and dispersion in directional datasets: the ellipsoidal cone covering approach," Journal of Global Optimization, Springer, vol. 68(2), pages 279-306, June.
    5. Edoardo Amaldi & Raphael Hauser, 2005. "Boundedness Theorems for the Relaxation Method," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 939-955, November.
    6. Daniele De Martino & Matteo Figliuzzi & Andrea De Martino & Enzo Marinari, 2012. "A Scalable Algorithm to Explore the Gibbs Energy Landscape of Genome-Scale Metabolic Networks," PLOS Computational Biology, Public Library of Science, vol. 8(6), pages 1-12, June.
    7. Daniel Dadush & László A. Végh & Giacomo Zambelli, 2020. "Rescaling Algorithms for Linear Conic Feasibility," Mathematics of Operations Research, INFORMS, vol. 45(2), pages 732-754, May.
    8. Robert M. Freund & Fernando Ordóñez, 2005. "On an Extension of Condition Number Theory to Nonconic Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 30(1), pages 173-194, February.
    9. Minh N. Dao, & Hung M. Phan, 2019. "Linear Convergence of Projection Algorithms," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 715-738, May.
    10. Freund, Robert & Ordonez, Fernando, 2003. "On an Extension of Condition Number Theory to Non-Conic Convex Optimization," Working papers 4286-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    11. Cheung, Dennis & Cucker, Felipe & Pea, Javier, 2009. "On strata of degenerate polyhedral cones I: Condition and distance to strata," European Journal of Operational Research, Elsevier, vol. 198(1), pages 23-28, October.
    12. H. H. Bauschke & S. G. Kruk, 2004. "Reflection-Projection Method for Convex Feasibility Problems with an Obtuse Cone," Journal of Optimization Theory and Applications, Springer, vol. 120(3), pages 503-531, March.

    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:273:y:2016:i:c:p:525-534. 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: 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.