Single node reconstruction of graph signal based on graph fractional Fourier transform

Zhenyang Yan; Yang Deng

doi:10.1117/12.2643492

9 October 2022 Single node reconstruction of graph signal based on graph fractional Fourier transform

Zhenyang Yan, Yang Deng

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122460M (2022) https://doi.org/10.1117/12.2643492
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

A general scheme to sample signals defined on the nodes of a graph is proposed. In this paper, we study the sampling and recovery of graph signals with successive local aggregations under the graph fractional Fourier transform. In the graph fractional Fourier domain, we show that fractional bandlimited graph signals can be perfectly recovered. Our focus is on reconstructing fractional bandlimited graph signals. This sampling strategy, unlike the graph's subset selection scheme, obtains observations from a single node. We give examples of graph signal sampling to demonstrate that fractional bandlimited graph signals can be perfectly recovered and compare it with graph aggregation sampling.

Citation Download Citation

Zhenyang Yan and Yang Deng "Single node reconstruction of graph signal based on graph fractional Fourier transform", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122460M (9 October 2022); https://doi.org/10.1117/12.2643492

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