FeeLab/seqNMF

An algorithm for unsupervised discovery of sequential structure
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Updated 17 Mar 2024

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 (2025). FeeLab/seqNMF (https://github.com/FeeLab/seqNMF), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
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Version Published Release Notes
1.0.0.0

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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.