IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v210y2023icp640-660.html
   My bibliography  Save this article

Solving Sturm–Liouville inverse problems by an orthogonalized enhanced boundary function method and a product formula for symmetric potential

Author

Listed:
  • Liu, Chein-Shan
  • Li, Botong

Abstract

We develop a fast convergence iterative method after transforming the Sturm–Liouville problem into the weak-form integral equations, and using sinusoidal functions as the testers as well as the bases of eigenfunction. Owing to the orthogonal property of these bases, we can obtain the expansion coefficients in closed-form. A new idea of orthogonalized and enhanced boundary function (OEBF) is introduced to compute eigenvalues. In the Sobolev space, we prove the closeness of the OEBF to the eigenfunction with their distance being reduced when the eigenvalue increases. Moreover, upon expressing the Rayleigh quotient in terms of OEBF, the unknown functions in the Sturm–Liouville operator can be recovered quickly, merely two boundary data of unknown functions and the first eigenvalue are sufficing. The OEBF is a promising method with a few iterations to obtain quite accurate estimations of the unknown potential and weight functions. Thanks to the symmetry property a symmetric matrix eigenvalue problem is derived to recover a symmetric potential. The characteristic equation endowing with a special coefficient matrix is decomposed into a product of two characteristic equations. The Newton iterative method is thus developed by relying on the product formula to reconstruct the unknown symmetric potential function with the aid of a few lower orders eigenvalues.

Suggested Citation

  • Liu, Chein-Shan & Li, Botong, 2023. "Solving Sturm–Liouville inverse problems by an orthogonalized enhanced boundary function method and a product formula for symmetric potential," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 640-660.
  • Handle: RePEc:eee:matcom:v:210:y:2023:i:c:p:640-660
    DOI: 10.1016/j.matcom.2023.03.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475423001301
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2023.03.025?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. Chein-Shan Liu & Jiang-Ren Chang & Jian-Hung Shen & Yung-Wei Chen, 2022. "A Boundary Shape Function Method for Computing Eigenvalues and Eigenfunctions of Sturm–Liouville Problems," Mathematics, MDPI, vol. 10(19), pages 1-22, October.
    2. Dehghan, M., 2016. "An efficient method to approximate eigenfunctions and high-index eigenvalues of regular Sturm–Liouville problems," Applied Mathematics and Computation, Elsevier, vol. 279(C), pages 249-257.
    3. Chein-Shan Liu, 2020. "Analytic Solutions of the Eigenvalues of Mathieu’s Equation," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 12(1), pages 1-1, February.
    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. Liu, Chein-Shan & Chen, Yung-Wei & Chang, Chih-Wen, 2024. "Precise eigenvalues in the solutions of generalized Sturm–Liouville problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 354-373.

    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:matcom:v:210:y:2023:i:c:p:640-660. 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: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.