Topic Editors
Theory and Application of Fractional Methods in Interdisciplinary Fields
Topic Information
Dear Colleagues,
With the continuous advancement of science and technology, signal processing techniques have experienced rapid development. Among them, fractional-domain signal processing methods—including, but not limited to, fractional calculus, the fractional Fourier transform (FrFT), linear canonical transform (LCT), and their variants—have attracted growing interest due to their ability to offer greater flexibility in time–frequency analysis, system modeling, and information processing.
In recent years, fractional-domain concepts have been extended to structured and irregular data domains such as graph signal processing and vertex–frequency analysis, enabling the exploration of signals on complex topologies like networks and manifolds. At the same time, fractional-domain statistical signal processing and machine learning techniques are emerging as powerful tools in modern data-driven and intelligent systems.
This Topic aims to highlight the latest advances in the theory, algorithms, and applications of fractional-domain methods across a wide range of signal and data processing tasks. We welcome original research articles and reviews that explore mathematical foundations, novel computational methods, or interdisciplinary applications. Contributions from applied mathematics, engineering, computer science, and related fields are encouraged.
Prof. Dr. Bingzhao Li
Prof. Dr. Mawardi Bahri
Prof. Dr. Zhi-Chao Zhang
Prof. Dr. Qiang Feng
Topic Editors
Keywords
- fractional-domain signal processing
- fractional fourier transform
- linear canonical transform
- graph signal processing
- time–frequency analysis
- machine learning
- complex networks
- fractional methods in data science
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
|---|---|---|---|---|---|---|
AppliedMath
|
0.7 | 1.4 | 2021 | 20.6 Days | CHF 1200 | Submit |
Axioms
|
1.6 | - | 2012 | 21.7 Days | CHF 2400 | Submit |
Computation
|
1.9 | 5.2 | 2013 | 14.8 Days | CHF 1800 | Submit |
Fractal and Fractional
|
3.3 | 6.8 | 2017 | 19.3 Days | CHF 2700 | Submit |
Mathematics
|
2.2 | 5.4 | 2013 | 17.3 Days | CHF 2600 | Submit |
Signals
|
2.6 | 5.9 | 2020 | 21.8 Days | CHF 1200 | Submit |
Symmetry
|
2.2 | 5.2 | 2009 | 15.8 Days | CHF 2400 | Submit |
Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.
MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:
- Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
- Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
- Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
- Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
- Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.