Time-Frequency Filtering Meets Graph Clustering

Marcelo A. Colominas, Stefan Steinerberger, Hau-Tieng Wu
10/8/2025
eess.SPcs.LG

No confident code implementation found for this paper.

Abstract

We show that the problem of identifying different signal components from a time-frequency representation can be equivalently phrased as a graph clustering problem: given a graph $G=(V,E)$ one aims to identify `clusters', subgraphs that are strongly connected and have relatively few connections between them. The graph clustering problem is well studied, we show how these ideas can suggest (many) new ways to identify signal components. Numerical experiments illustrate the ideas.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Clustering of Time-Varying Graphs Based on Temporal Label Smoothness

82% match2023

Transfer operators on graphs: Spectral clustering and beyond

80% match2023

Advanced Graph Clustering Methods: A Comprehensive and In-Depth Analysis

80% match1 repo62024

k-Graph: A Graph Embedding for Interpretable Time Series Clustering

80% match1 repo462025

Clustering Time-Evolving Networks Using the Spatio-Temporal Graph Laplacian

79% match2024

Provable Filter for Real-world Graph Clustering

79% match2024

Cite this paper

@article{colominas2025timefrequency,
  title  = {Time-Frequency Filtering Meets Graph Clustering},
  author = {Marcelo A. Colominas and Stefan Steinerberger and Hau-Tieng Wu},
  year   = {2025},
  eprint = {2510.07503},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.07503v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2510.07503.svg)](https://codeofpaper.com/paper/2510.07503)

Discussion