Low-Bit Quantization of Bandlimited Graph Signals via Iterative Methods

Fuente: arXiv
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Autores principales: Krahmer, Felix, Lyu, He, Saab, Rayan, Qian, Jinna, Veselovska, Anna, Wang, Rongrong
Formato: Preprint
Publicado: 2026
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author Krahmer, Felix
Lyu, He
Saab, Rayan
Qian, Jinna
Veselovska, Anna
Wang, Rongrong
author_facet Krahmer, Felix
Lyu, He
Saab, Rayan
Qian, Jinna
Veselovska, Anna
Wang, Rongrong
contents We study the quantization of real-valued bandlimited signals on graphs, focusing on low-bit representations. We propose iterative noise-shaping algorithms for quantization, including sampling approaches with and without vertex replacement. The methods leverage the spectral properties of the graph Laplacian and exploit graph incoherence to achieve high-fidelity approximations. Theoretical guarantees are provided for the random sampling method, and extensive numerical experiments on synthetic and real-world graphs illustrate the efficiency and robustness of the proposed schemes.
format Preprint
id arxiv_https___arxiv_org_abs_2601_18782
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Low-Bit Quantization of Bandlimited Graph Signals via Iterative Methods
Krahmer, Felix
Lyu, He
Saab, Rayan
Qian, Jinna
Veselovska, Anna
Wang, Rongrong
Signal Processing
Numerical Analysis
Image and Video Processing
Group Theory
Optimization and Control
42C15, 94A12, 05C50, 94A29
G.1.2; E.4; G.2.2
We study the quantization of real-valued bandlimited signals on graphs, focusing on low-bit representations. We propose iterative noise-shaping algorithms for quantization, including sampling approaches with and without vertex replacement. The methods leverage the spectral properties of the graph Laplacian and exploit graph incoherence to achieve high-fidelity approximations. Theoretical guarantees are provided for the random sampling method, and extensive numerical experiments on synthetic and real-world graphs illustrate the efficiency and robustness of the proposed schemes.
title Low-Bit Quantization of Bandlimited Graph Signals via Iterative Methods
topic Signal Processing
Numerical Analysis
Image and Video Processing
Group Theory
Optimization and Control
42C15, 94A12, 05C50, 94A29
G.1.2; E.4; G.2.2
url https://arxiv.org/abs/2601.18782