GSD
1.0.0Graph Signal Decomposition
Overview
Graph signals residing on the vertices of a graph have recently gained prominence in research in various fields. Many methodologies have been proposed to analyze graph signals by adapting classical signal processing tools. Recently, several notable graph signal decomposition methods have been proposed, which include graph Fourier decomposition based on graph Fourier transform, graph empirical mode decomposition, and statistical graph empirical mode decomposition. This package efficiently implements multiscale analysis applicable to various fields, and offers an effective tool for visualizing and decomposing graph signals. For the detailed methodology, see Ortega et al. (2018) doi:10.1109/JPROC.2018.2820126, Shuman et al. (2013) doi:10.1109/MSP.2012.2235192, Tremblay et al. (2014) https://www.eurasip.org/Proceedings/Eusipco/Eusipco2014/HTML/papers/1569922141.pdf, and Cho et al. (2024) "Statistical graph empirical mode decomposition by graph denoising and boundary treatment".
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- References docs
- 60%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 3.5 median / 49 max
Test coverage
Line coverage
–
Expression
–
Tests / Examples
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Functions
10 9 exported
Complexity
12.1 avg / 49 max
Call network
10 nodes / 3 edges
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2024-02-05
- Total releases
- 1 / 2 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 7.7 KB / 1 file
- Download size
- 22 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet