josemateosramos/SSLISAC
Semi-Supervised End-to-End Learning for Integrated Sensing and Communications
This tool helps researchers and engineers working on wireless communication systems design and optimization. It takes raw sensing and communication data and processes it using various machine learning techniques to improve the efficiency and performance of integrated sensing and communication (ISAC) systems. It's ideal for those developing next-generation wireless technologies.
No commits in the last 6 months.
Use this if you are a researcher or engineer looking to explore and apply semi-supervised learning methods to enhance the capabilities of integrated sensing and communication systems.
Not ideal if you need an out-of-the-box solution for deploying a real-world ISAC system, as this is a research-focused development tool.
Stars
21
Forks
7
Language
Python
License
GPL-3.0
Category
Last pushed
Jan 11, 2024
Commits (30d)
0
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