This rep contains jupyter notebooks for teaching mathematical foundations of signal processing.
For simplicity, you can run the notebooks using Binder: https://mybinder.org/v2/gh/adamscholefield/MFSP_notebooks/master
Alternatively, if you wish to run the notebooks locally, a list of required packages is given in the requirements.txt.
The following notebooks are included:
- Finite dimensional inverse problems: a geometrical perspective
- FRI simple: a basic Anihilatig Filter example
- Basis Expansion: visualsiation and orthogonalisation of bases of function spaces
- Projections: approximating functions with help of projection theorem
If you want to contribute to this repository, you should run:
./scripts/setup_repository
after downloading the repository, in order to set up yapf formatter and git
hook for removing non important changes and outputs form Jupyter Notebooks.