Welcome to this repository dedicated to signal processing and source separation techniques! Here, you'll find a collection of Jupyter Notebook files covering various methods, including Independent Component Analysis (ICA), Laccume algorithms, and more.
- Geometric_ICA.ipynb: Notebook exploring a geometric approach for separating signals using ICA.
- Laccume.ipynb: Notebook implementing the Laccume algorithm for source separation.
- Additional notebooks: Explore more techniques for signal processing and source separation.
A Geometric Approach for Separating Several Signals in this work, we want to use a geometric approach to separate two signals that are statistically independent.
BASED ON THIS ARTICLE: A Geometric Approach for Separating Several Speech Signals
Massoud Babaie-Zadeh1,2, Ali Mansour3, Christian Jutten4, and Farrokh Marvasti1,2 1 Multimedia Lab, Iran Telecom Research Center (ITRC), Tehran, Iran mbzadeh@yahoo.com, marvasti@itrc.ac.ir 2 Electrical Engineering Department, Sharif University of Technology, Tehran, Iran 3 E3I2, ENSIETA, Brest, France mansour@ieee.org 4 Institut National Polytechnique de Grenoble (INPG), Laboratoire des Images et des Signaux (LIS), Grenoble, France Christian.Jutten@inpg.fr
This work has been partially funded by the European project Blind Source Separation and applications (BLISS, IST 1999-14190), by Iran Telecom Research Center (ITRC), and by Sharif University of Technology.
Feel free to delve into the notebooks, experiment with the code, and apply these techniques to your own signal processing tasks!
If you have any questions or suggestions for improvements, please don't hesitate to reach out.
Happy coding! 🚀