FeeLab/seqNMF
An algorithm for unsupervised discovery of sequential structure
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SeqNMF is an algorithm which uses regularized convolutional non-negative matrix factorization to extract repeated sequential patterns from high-dimensional data. It has been validated using neural calcium imaging, spike data, and spectrograms, and allows the discovery of patterns directly from timeseries data without reference to external markers.
For more information see our preprint: https://www.biorxiv.org/content/early/2018/03/02/273128
Cite As
SeqNMF FeeLab (2026). FeeLab/seqNMF (https://github.com/FeeLab/seqNMF), GitHub. Retrieved .
General Information
- Version 1.0.0.0 (4.54 MB)
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View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
Versions that use the GitHub default branch cannot be downloaded
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
adding picture
|
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.
