graph-laplacian-denoising
CommunityDenoise brain graphs to boost FC and BCI.
Education & Research#laplacian#eeg#brain-connectivity#functional-connectivity#graph-denoising#brain-state-classification#j-divergence
Authorhiyenwong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill denoises functional connectivity graphs derived from EEG data to improve the reliability of connectivity estimates and downstream brain-state detection.
Core Features & Use Cases
- Graph Laplacian representation of connectivity matrices.
- Spectral denoising to emphasize smooth, meaningful structure while reducing noise.
- Jensen divergence-based similarity assessment to compare connectivity states.
- Real-time brain-computer interface and clinical network analysis workflows.
Quick Start
Load your functional connectivity matrix and run the graph Laplacian denoising pipeline to produce a denoised Laplacian and updated FC estimates.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: graph-laplacian-denoising Download link: https://github.com/hiyenwong/ai_collection/archive/main.zip#graph-laplacian-denoising Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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