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# Signals CNN To run the network, change any variables in `main.py` and run. The script will save both the network model (the actual structure of the neurons/layers) in a JSON file, and its corresponding weights in a H5 file. To visualize, run the `visualize.py` script. The visualization script reads from a very small subset of our full dataset. This can be located in the `small_dataset` directory. The `data_processing` directory holds MATLAB scripts that actually processed data from GNURadio. The `models` directory holds a bunch of pre-trained networks on the main dataset. The `Conv8` model was trained on the entire dataset with a kernel size of `(1, 1)` in the convolutional layers. The `BigKernel8` model was also trained on the dataset, but the first Conv2D layer had a kernel size of (2, 2). A README can be found inside the `models/mod` directory further detailing the models.
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