Author: Rémi Carloni Gertosio
Year: 2020
Email: remi.carlonigertosio@cea.fr
The goal of this tutorial is to present Blind Source Separation (BSS) problems and the main methods to solve them. This tutorial does not provide in-depth mathematical explanations for every methods; the emphasis is rather on illustrations and intuition.
- Introduction
- Principal Component Analysis
- Independant Component Analysis
- Non-negative matrix factorization
- Sparse matrix factorization: the GMCA example
- BSS with pictures
This tutorial was written with Python 3.7. The following Python libraries need to be installed to run the tutorial:
- NumPy,
- Matplotlib,
- SciPy,
- Scikit-Learn,
- Jupyter.
The author would like to thank J. Bobin for BSS materials and helpful feedback for producing this tutorial.