Theory and Application of Fractional Methods in Interdisciplinary Fields

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