This is an implementation for paper Linearly constraint Bayesian Matrix Factorization for Blind Source Separation
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Updated
Dec 20, 2021 - Python
This is an implementation for paper Linearly constraint Bayesian Matrix Factorization for Blind Source Separation
Different Tasks with Neural Networks
Convex Analysis of Mixture Non-negative Sources implementation in Python
Audio components classification for video audio tagging. Utilizes Microsoft CLAP and Separate Anything You Describe multi-modal LLMs.
Mutual information least-dependent component analysis
An exercise on the use of NMF for Blind Signal Separation
Python implementation of Stone's blind source separation algorithm. Refer to his paper (cited in README) for details.
An unsupervised clustering techniques to understand if any similarities exist between customers and use those similarities to segment customers into distinct categories
Audio Unmixing and Music Score Transcription. Developed as my undergraduate final year project.
Mutual information least-dependent component analysis
Topographical Representation in an Associative Learning Task Using BSS Analysis on MEG Signals
Tutorial on Independent Component Analysis
SDecGMCA open-source code
wGMCA open-source code
2DecGMCA open-source code (2D adaptation of SDecGMCA)
Blind Separation of Sparse Signals Diffused on Graphs
For collaboration in ECSE 444
Localization of brain sources measured by EEG using 3 approaches: Gibbs sampler (Markov chain Monte Carlo algorithm), Minimum Norm Estimates (MNE) and Source Imaging based on Structured Sparsity (SISSY)
Retina Imaging Toolbox (RIT)
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