Beyond Single-Window Graph Fourier Analysis

Fuente: arXiv
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Auteurs principaux: Bulai, Iulia Martina, Cordero, Elena, Pucci, Edoardo, Saliani, Sandra
Format: Preprint
Publié: 2026
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author Bulai, Iulia Martina
Cordero, Elena
Pucci, Edoardo
Saliani, Sandra
author_facet Bulai, Iulia Martina
Cordero, Elena
Pucci, Edoardo
Saliani, Sandra
contents We introduce a multi-windowed graph Fourier transform (MWGFT) for the joint vertex-frequency analysis of signals defined on graphs. Building on generalized translation and modulation induced by the graph Laplacian, the proposed framework extends the windowed graph Fourier transform by allowing multiple analysis and synthesis windows. Exact reconstruction formulas are derived for complex-valued graph signals, together with sufficient and computable conditions guaranteeing stable invertibility. The associated families of windowed graph Fourier atoms are shown to form frames for the space of graph signals. Numerical experiments on synthetic and real world graphs confirm exact reconstruction up to machine precision and demonstrate improved stability and vertex-frequency localization compared to single-window constructions, particularly on irregular graph topologies.
format Preprint
id arxiv_https___arxiv_org_abs_2601_19009
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Beyond Single-Window Graph Fourier Analysis
Bulai, Iulia Martina
Cordero, Elena
Pucci, Edoardo
Saliani, Sandra
Classical Analysis and ODEs
Signal Processing
We introduce a multi-windowed graph Fourier transform (MWGFT) for the joint vertex-frequency analysis of signals defined on graphs. Building on generalized translation and modulation induced by the graph Laplacian, the proposed framework extends the windowed graph Fourier transform by allowing multiple analysis and synthesis windows. Exact reconstruction formulas are derived for complex-valued graph signals, together with sufficient and computable conditions guaranteeing stable invertibility. The associated families of windowed graph Fourier atoms are shown to form frames for the space of graph signals. Numerical experiments on synthetic and real world graphs confirm exact reconstruction up to machine precision and demonstrate improved stability and vertex-frequency localization compared to single-window constructions, particularly on irregular graph topologies.
title Beyond Single-Window Graph Fourier Analysis
topic Classical Analysis and ODEs
Signal Processing
url https://arxiv.org/abs/2601.19009