https://github.com/sylvchev/riemannianpca

Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
https://github.com/sylvchev/riemannianpca

covariance eeg pca pymanopt riemannian-manifold

Last synced: about 1 month ago
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Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation

• Host: GitHub
• URL: https://github.com/sylvchev/riemannianpca
• Owner: sylvchev
• License: bsd-3-clause
• Created: 2023-04-04T00:01:34.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-04-18T15:50:41.000Z (over 1 year ago)
• Last Synced: 2023-08-05T09:04:04.351Z (over 1 year ago)
• Topics: covariance, eeg, pca, pymanopt, riemannian-manifold
• Language: Python
• Homepage:
• Size: 12.7 KB
• Stars: 7
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# RiemannianPCA

Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation

# Reference

This project proposes an implementation of 

> Harandi, M, Salzmann, M., Hartley, R., 

> Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods, 

> preprint [arXiv:1605.06182](https://arxiv.org/pdf/1605.06182.pdf)

and 

> Rodrigues, P. L. C., Bouchard, F., Congedo, M., & Jutten, C. (2017, September). 

> Dimensionality Reduction for BCI classification using Riemannian geometry. 

> In BCI 2017-7th [International Brain-Computer Interface Conference](https://hal.archives-ouvertes.fr/hal-01591258/document).