Manuscript Topics

With the rapid development of modern signal processing theory, the processed signal has gradually developed from relatively simple and stable signals to more complex signals, such as non-stationary, non-Gaussian, non-single sampling complex signal and time-varying. Applied mathematics in information theory and signal processing focuses on transformation tools, spectrum estimation and optimization algorithms in applied mathematics, such as Fourier transform, fractional-order transform, compressive sensing, detection and estimation etc., to process modern complex signals and large-scale data in information systems, as well as high-dimensional data with complex irregular topological structures.
Traditional signal processing theories and methods can no longer meet practical needs. The fractional Fourier transform is a representative tool for fractional order signal processing. It uses a set of linear frequency-modulated orthogonal bases to decompose signals, making it suitable for processing non-stationary signals. The theory and methods of fractional order signal processing are favored by many researchers due to their unique characteristics. At present, the theory of fractional order transformation has been widely used in many fields of scientific research and engineering technology, such as time-frequency analysis, time-varying filtering, partial differential equations, complex transmission, data transmission and compression, spectrum estimation, artificial neural network, etc. In addition, with the demand for big data and real-time signal processing, sparse fractional Fourier transform and expansions have been developed and widely applied in spectral sensing, image recognition and fusion, compressed sampling, and sparse representation. With the continuous emergence of large-scale and high-dimensional signals, the graph signal processing has been developed.
This Special Issue aims to continue to advance research on topics relating to the theory, algorithm development and application of fractional order signal processing.

The topics for invitation submission include (but are not limited to) the following:

• Mathematical theory of fractional-order transform;
• Numerical algorithm of fractional-order transform;
• Sparse representation and fast algorithm;
• Sparse Fourier transform and its applications;
• Sparse fractional order signal processing;
• Graph fractional Fourier transform and its applications;
• Graph sampling theory and methods;
• Graph neural networks and their applications;
• Applications of fractional-order transform in signal processing, information security, image processing and other fields.

Instructions for authors
https://www.aimspress.com/math/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/