brysef/rfml
Radio Frequency Machine Learning with PyTorch
This project helps wireless communication engineers and researchers classify radio frequency (RF) signals using deep learning. It takes raw signal data, often from publicly available datasets, and processes it to train and evaluate deep neural networks. The output includes classification accuracies and confusion matrices, enabling users to understand how well their models identify different signal types.
184 stars. No commits in the last 6 months.
Use this if you are a researcher or engineer in wireless communications looking to apply or develop machine learning techniques for signal classification and related tasks, particularly using PyTorch.
Not ideal if you are a beginner in machine learning or deep learning and need a no-code solution, or if you are not working with radio frequency signal data.
Stars
184
Forks
57
Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Sep 24, 2024
Commits (30d)
0
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