A short-graph fourier transform via personalized pagerank vectors

Conference Paper

The short-time Fourier transform (STFT) is widely used to analyze the spectra of temporal signals that vary through time. Signals defined over graphs, due to their intrinsic complexity, exhibit large variations in their patterns. In this work we propose a new formulation for an STFT for signals defined over graphs. This formulation draws on recent ideas from spectral graph theory, using personalized PageRank vectors as its fundamental building block. Furthermore, this work establishes and explores the connection between local spectral graph theory and localized spectral analysis of graph signals. We accompany the presentation with synthetic and real-world examples, showing the suitability of the proposed approach.

Full Text

Duke Authors

Cited Authors

  • Tepper, M; Sapiro, G

Published Date

  • May 18, 2016

Published In

Volume / Issue

  • 2016-May /

Start / End Page

  • 4806 - 4810

International Standard Serial Number (ISSN)

  • 1520-6149

International Standard Book Number 13 (ISBN-13)

  • 9781479999880

Digital Object Identifier (DOI)

  • 10.1109/ICASSP.2016.7472590

Citation Source

  • Scopus