Subsampling for graph power spectrum estimation

Sundeep Prabhakar Chepuri, Geert Leus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations


In this paper we focus on subsampling stationary random signals that reside on the vertices of undirected graphs. Second-order stationary graph signals are obtained by filtering white noise and they admit a well-defined power spectrum. Estimating the graph power spectrum forms a central component of stationary graph signal processing and related inference tasks. We show that by sampling a significantly smaller subset of vertices and using simple least squares, we can reconstruct the power spectrum of the graph signal from the subsampled observations, without any spectral priors. In addition, a near-optimal greedy algorithm is developed to design the subsampling scheme.
Original languageEnglish (US)
Title of host publication2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)9781509021031
StatePublished - Oct 6 2016
Externally publishedYes


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