@inproceedings{81e95a7b0f994d5196bf65c9537d948c,
title = "The fractional fourier transform on graphs: Sampling and recovery",
abstract = "Signal processing on graphs expands discrete signal processing theory and techniques to signals supported on graphs. In this paper, we study the sampling and recovery of graph signals under the graph fractional Fourier transform. We show that a-bandlimited signals in the graph fractional Fourier domain can be perfectly recovered. Experimentally designed sampling strategy is used to generate optimal fractional sampling operators on graphs. We give numerical examples, and test the semi-supervised classification of online blogs and handwritten digits using fractional sampling on graphs, and compare it with GFT sampling. We find that fractional sampling on graphs can lead to better classification accuracy at an optimal fractional order.",
keywords = "Sampling theory, Semi-supervised learning, Signal processing on graphs, The fractional Fourier transform",
author = "Yiqian Wang and Bingzhao Li",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 14th IEEE International Conference on Signal Processing, ICSP 2018 ; Conference date: 12-08-2018 Through 16-08-2018",
year = "2019",
month = feb,
day = "2",
doi = "10.1109/ICSP.2018.8652296",
language = "English",
series = "International Conference on Signal Processing Proceedings, ICSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1103--1108",
editor = "Yuan Baozong and Ruan Qiuqi and Zhao Yao and An Gaoyun",
booktitle = "2018 14th IEEE International Conference on Signal Processing Proceedings, ICSP 2018",
address = "United States",
}