Fractional Calculus in Signal, Imaging Processing and Machine Learning
A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".
Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 10979
Special Issue Editor
Interests: application of fractional calculus and fractional partial differential equation to signal analysis; signal processing; image processing; circuits and systems; machine intelligence
Special Issue Information
Dear Colleagues,
Fractional-order intelligent information processing refers to many fields of science and engineering that incorporate concepts from fractional calculus into their modeling and design. Fractional calculus is a generalization of the classical integer-order differentiation and integration theory. The theory and application of fractional calculus show that the fractional calculus operator is the best description for many complex natural or social phenomena. The fractional order can provide additional freedom of design for various applications. Due to its many unique characteristics, fractional calculus is being widely explored across many fields, such as signal processing, image processing, machine learning, etc. Additionally, fractional calculus is also being explored in computing law, neuromorphic computing, etc.
The focus of this Special Issue is to continue to advance research on topics relating to fractional calculus in signal processing, image processing, and machine learning. Topics that are invited for submission include (but are not limited to):
- Fractional-order signal processing;
- Fractional-order image processing;
- Fractional-order machine learning;
- Fractional-order computing law;
- Fractional-order neuromorphic computing.
Prof. Dr. Yifei Pu
Guest Editor
Manuscript Submission Information
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