JOURNAL ARTICLE
Mathematical model for wireless communication via microstrip antennas involving contemporary operators.
Published In: International Journal of Modeling, Simulation & Scientific Computing, 2026, v. 17, n. 1. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Alsisi, Rayan Hamza; Nuruddeen, Rahmatullah Ibrahim; Gómez-Aguilar, J. F.; Helmi, Maha M.; Mubaraki, Ali M. 3 of 3
Abstract
This study deploys certain contemporary fractional differential operators to model the transmission of electrical signals in microstrip antennas. Indeed, the study is motivated by the recorded progress in the present-day communication industries and on the other hand, the imperativeness of the futuristic outlook of the dissemination of digital information. Method-wise, the well-known iterative approach, which equally doubles as a numerical method by the name Adomian decomposition method is adopted alongside the eminent Laplace transform method for the examination of the governing class of differential equations. Lastly, the study validated the derived respective schemes for the antenna model amidst several spatial differential and fractional operators, and further numerically portrayed the variational influence of the involving spatial orders; in addition, a comparative analysis with regard to the beseeched contemporary fractional operators has been established. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modeling, Simulation & Scientific Computing. 2026/02, Vol. 17, Issue 1, p1
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2026
- ISSN:17939623
- DOI:10.1142/S1793962325500722
- Accession Number:192050550
- Copyright Statement:Copyright of International Journal of Modeling, Simulation & Scientific Computing is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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