@inproceedings{e16cc1eac8894754a24f84d7e3ae0f00,
title = "The fractional Fourier transform on graphs",
abstract = "The emerging field of signal processing on graphs merges algebraic or spectral graph theory with discrete signal processing techniques to process signals on graphs. In this paper, a definition of the fractional Fourier transform on graphs (GFRFT) is proposed and consolidated, which extends the discrete fractional Fourier transform (DFRFT) in the same sense the graph Fourier transform (GFT) extends the discrete Fourier transform (DFT). The definition is based on the eigenvalue decomposition method of defining DFRFT, for it satisfies all the agreeable properties expected of the discrete fractional Fourier transform. Properties of the GFRFT are discussed, and examples of GFRFT of some graph signals are given to illustrate the transform.",
author = "Wang, {Yi Qian} and Li, {Bing Zhao} and Cheng, {Qi Yuan}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/APSIPA.2017.8282010",
language = "English",
series = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "105--110",
booktitle = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",
address = "United States",
}