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A SHORT-GRAPH FOURIER TRANSFORM VIA PERSONALIZED PAGERANK VECTORS

Citation Author(s):
Mariano Tepper, Guillermo Sapiro
Submitted by:
Mariano Tepper
Last updated:
19 March 2016 - 4:23am
Document Type:
Poster
Document Year:
2016
Event:
Presenters:
Mariano Tepper
 

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.

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