IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i2p271-d725998.html
   My bibliography  Save this article

Lattice Computing: A Mathematical Modelling Paradigm for Cyber-Physical System Applications

Author

Listed:
  • Vassilis G. Kaburlasos

    (Human-Machines Interaction Laboratory (HUMAIN-Lab), Department of Computer Science, International Hellenic University (IHU), 65404 Kavala, Greece)

Abstract

By “model”, we mean a mathematical description of a world aspect [...]

Suggested Citation

  • Vassilis G. Kaburlasos, 2022. "Lattice Computing: A Mathematical Modelling Paradigm for Cyber-Physical System Applications," Mathematics, MDPI, vol. 10(2), pages 1-3, January.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:2:p:271-:d:725998
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/2/271/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/2/271/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francisco J. Valverde-Albacete & Carmen Peláez-Moreno, 2020. "The Singular Value Decomposition over Completed Idempotent Semifields," Mathematics, MDPI, vol. 8(9), pages 1-39, September.
    2. Marcos Eduardo Valle, 2020. "Reduced Dilation-Erosion Perceptron for Binary Classification," Mathematics, MDPI, vol. 8(4), pages 1-21, April.
    3. Chris Lytridis & Anna Lekova & Christos Bazinas & Michail Manios & Vassilis G. Kaburlasos, 2020. "WINkNN: Windowed Intervals’ Number kNN Classifier for Efficient Time-Series Applications," Mathematics, MDPI, vol. 8(3), pages 1-14, March.
    4. Gerhard X. Ritter & Gonzalo Urcid & Luis-David Lara-Rodríguez, 2020. "Similarity Measures for Learning in Lattice Based Biomimetic Neural Networks," Mathematics, MDPI, vol. 8(9), pages 1-18, August.
    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. Emmanouil Tziolas & Eleftherios Karapatzak & Ioannis Kalathas & Chris Lytridis & Spyridon Mamalis & Stefanos Koundouras & Theodore Pachidis & Vassilis G. Kaburlasos, 2023. "Comparative Assessment of Environmental/Energy Performance under Conventional Labor and Collaborative Robot Scenarios in Greek Viticulture," Sustainability, MDPI, vol. 15(3), pages 1-21, February.

    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. Mariya Kornilova & Vladislav Kovalnogov & Ruslan Fedorov & Mansur Zamaleev & Vasilios N. Katsikis & Spyridon D. Mourtas & Theodore E. Simos, 2022. "Zeroing Neural Network for Pseudoinversion of an Arbitrary Time-Varying Matrix Based on Singular Value Decomposition," Mathematics, MDPI, vol. 10(8), pages 1-12, April.

    More about this item

    Keywords

    n/a;

    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:gam:jmathe:v:10:y:2022:i:2:p:271-:d:725998. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.