dissertation/where_fi
Christos Falas c452e44e1a
MUSIC eigenvalue visualisation
One of the issues I've been facing was that the range of the eigenvalues
was quite large, and I couldn't easily see a natural threshold to set to
separate the signal and noise subspaces.

This visualisation provides a histogram for this scenario, to assist in
choosing the parameter (which is different in different configurations).
2025-03-04 13:48:32 +00:00
..
cli MUSIC eigenvalue visualisation 2025-03-04 13:48:32 +00:00
collection set up torch AoA estimation 2025-01-30 13:58:08 +02:00
config Allow skipping subcarriers 2025-02-11 11:16:27 +00:00
processing MUSIC eigenvalue visualisation 2025-03-04 13:48:32 +00:00
utils improve antenna order detection 2025-02-24 15:02:21 +00:00
visualise MUSIC eigenvalue visualisation 2025-03-04 13:48:32 +00:00
__init__.py Make into package 2025-01-27 15:55:17 +00:00
__main__.py Make into package 2025-01-27 15:55:17 +00:00