Recent Advances in Fractional-Order Time Delay Systems

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "General Mathematics, Analysis".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 1302

Special Issue Editors

College of Science, Northwest A&F University, Xianyang 712100, China
Interests: fractional-order neural networks; fractional-order complex networks
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Guest Editor
College of Science, Northwest A&F University, Xianyang 712100, China
Interests: dynamic behavior analysis of fractional order systems and its application in information security

Special Issue Information

Dear Colleagues,

The theory of fractional-order calculus has been successfully applied to various fields, and it can describe some non-classical phenomena in natural science and engineering. Fractional-order models are a powerful tool for advancing scientific research in these fields. Time delays often appear in the states, the control inputs, or the measurements in many real systems. The existence of time delays often leads to undesirable dynamic behaviors, or even destroys the stability. Therefore, we hope that researchers will discuss various applications of fractional-order time delay systems and thereby inspire readers in this Special Issue.

The purpose of this Special Issue is mainly to gather some up-to-date research results on recent advances in the theory and application of stability analysis and stabilization of fractional-order time delay systems. We invite the authors to submit original research articles and high-quality review articles in fractional order time delay systems obtained from the development, analysis, and simulation of mathematical models.

The focus of this Special Issue is to continue to advance research on topics relating to the theory, design, implementation, and application of fractional-order time delay systems. Topics that are invited for submission include (but are not limited to):

  • Explicit solution of the discrete-time fractional-order time delay systems;
  • Explicit solution of the continuous-time fractional-order time delay systems;
  • Modeling and application of fractional-order model with time delays;
  • Stability and synchronization of fractional-order complex networks with time delays;
  • Stability and synchronization of fractional-order neural networks with time delays.

Dr. Feifei Du
Dr. Zeyu Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fractal and Fractional is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fractional-order systems
  • complex networks
  • neural networks
  • time delay
  • stability
  • synchronization

Published Papers (1 paper)

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Research

15 pages, 408 KiB  
Article
New Approach to Quasi-Synchronization of Fractional-Order Delayed Neural Networks
by Shilong Zhang, Feifei Du and Diyi Chen
Fractal Fract. 2023, 7(11), 825; https://doi.org/10.3390/fractalfract7110825 - 16 Nov 2023
Viewed by 975
Abstract
This article investigates quasi-synchronization for a class of fractional-order delayed neural networks. By utilizing the properties of the Laplace transform, the Caputo derivative, and the Mittag–Leffler function, a new fractional-order differential inequality is introduced. Furthermore, an adaptive controller is designed, resulting in the [...] Read more.
This article investigates quasi-synchronization for a class of fractional-order delayed neural networks. By utilizing the properties of the Laplace transform, the Caputo derivative, and the Mittag–Leffler function, a new fractional-order differential inequality is introduced. Furthermore, an adaptive controller is designed, resulting in the derivation of an effective criterion to ensure the aforementioned synchronization. Finally, a numerical illustration is provided to demonstrate the validity of the presented theoretical findings. Full article
(This article belongs to the Special Issue Recent Advances in Fractional-Order Time Delay Systems)
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