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Title: Wide-sense stationarity in generalized graph signal processing
Authors: Jian, Xingchao
Tay, Wee Peng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Jian, X. & Tay, W. P. (2022). Wide-sense stationarity in generalized graph signal processing. IEEE Transactions On Signal Processing, 70, 3414-3428.
Project: MOE-T2EP20220-0002
Journal: IEEE Transactions on Signal Processing
Abstract: We consider statistical graph signal processing (GSP) in a generalized framework where each vertex of a graph is associated with an element from a Hilbert space. This general model encompasses various signals such as the traditional scalar-valued graph signal, multichannel graph signal, and discrete- and continuous-time graph signals, allowing us to build a unified theory of graph random processes. We introduce the notion of joint wide-sense stationarity in this generalized GSP framework, which allows us to characterize a graph random process as a combination of uncorrelated oscillation modes across both the vertex and Hilbert space domains. We elucidate the relationship between the notions of wide-sense stationarity in different domains, and derive the Wiener filters for denoising and signal completion under this framework. Numerical experiments on both real and synthetic datasets demonstrate the utility of our generalized approach in achieving better estimation performance compared to traditional GSP or the time-vertex framework.
ISSN: 1053-587X
DOI: 10.1109/TSP.2022.3184455
Schools: School of Electrical and Electronic Engineering 
Research Centres: Centre for Infocomm Technology (INFINITUS) 
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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