IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v524y2026ics0096300326000937.html

Inequality, uncertainty principles and their structural analysis for offset linear canonical transform and its quaternion extension

Author

Listed:
  • Rani Mahato, Gita
  • Varghese, Sarga
  • Kundu, Manab

Abstract

This work undertakes a twofold investigation. In the first part, we examine the inequalities and uncertainty principles in the framework of offset linear canonical transform (OLCT), with particular attention to its scaling and shifting effects. Theoretical developments are complemented by numerical simulations that substantiate and illustrate the analytical results. In the second part, we establish the connection of quaternion offset linear canonical transform (QOLCT) and the OLCT by employing the orthogonal plane split (OPS) approach. Through this approach, the inequalities and uncertainty principles derived for the OLCT are extended to the QOLCT. Moreover, the computational methods designed for the OLCT may systematically adapted to facilitate the numerical implementation of the QOLCT using this connection between OLCT and QOLCT.

Suggested Citation

  • Rani Mahato, Gita & Varghese, Sarga & Kundu, Manab, 2026. "Inequality, uncertainty principles and their structural analysis for offset linear canonical transform and its quaternion extension," Applied Mathematics and Computation, Elsevier, vol. 524(C).
  • Handle: RePEc:eee:apmaco:v:524:y:2026:i:c:s0096300326000937
    DOI: 10.1016/j.amc.2026.130041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300326000937
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2026.130041?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:apmaco:v:524:y:2026:i:c:s0096300326000937. 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.