Fractional Fourier Transform and Its Applications in Signal Analysis

Dear Colleagues,

With the rapid development of the information technology, the research object of signal processing gradually shifts from relatively simple and stable signals to more complex signals such as non-stationary, non-Gaussian, and time-varying. The fractional Fourier transform uses a set of linear frequency modulated orthogonal bases to decompose the signal, which makes it suitable for processing non-stationary signals. Therefore, fractional Fourier transform is highly favored by researchers in signal analysis such as signal separation, signal filtering, signal detection, and signal estimation. With the demand for big data and real-time signal processing, sparse fractional Fourier transform and expansions, as well as fast algorithms, have been developed and widely applied in radar signal processing, spectral sensing, image recognition and fusion, compressed sampling, and sparse representation. With the continuous emergence of large-scale and high-dimensional signals, two-dimensional fractional Fourier transform and its extensions, as well as graph fractional Fourier transform, have been developed. This has also been widely applied in many fields such as two-dimensional digital signal processing, image super-resolution reconstruction, image encryption and watermarking, medical imaging, image compression, image classification, semi supervised learning, and so on.

This Special Issue aims to continue the research on the theory of fractional Fourier transform and related extended theories, discrete and sparse fast algorithms, and their related applications. The topics for invitation submission include (but are not limited to) the following:

• Mathematical theory of FRFT;
• Sparse representation and fast algorithm;
• Sparse fractional Fourier transform and its applications;
• Graph fractional Fourier transform and its applications;
• Applications of FRFT in signal processing, information security and other fields;
• Applications of two-dimensional FRFT in image processing and other fields.

Dr. Yuan-Min Li
Prof. Dr. Deyun Wei
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.

• fractional Fourier transform
• linear canonical transform
• sparse fractional Fourier transform
• graph fractional Fourier transform
• fast Fourier transform
• sampling theory
• convolution and filtering
• digital signal processing