About TorchSig

An Open-Source Toolkit

TorchSig is an open-source signal processing machine learning toolkit based on the PyTorch data handling pipeline. The user-friendly toolkit simplifies common digital signals processing operations, augmentations, and transformations when dealing with both real and complex-valued signals. Building on PyTorch functionality, TorchSig streamlines the integration process of these signals processing tools, enabling faster and easier research and development of deep learning techniques applied to signals data, particularly within (but not limited to) the radio frequency domain. An example dataset based on many unique and common signal modulations is also included to accelerate the field of modulation recognition.

Referencing TorchSig

To reference TorchSig, please use the provided BibTeX for our paper.

                                
@misc{torchsig,
  title={Large Scale Radio Frequency Signal Classification},
  author={Luke Boegner and Manbir Gulati and Garrett Vanhoy and Phillip Vallance and Bradley Comar and Silvija Kokalj-Filipovic and Craig Lennon and Robert D. Miller},
  year={2022},
  archivePrefix={arXiv},
  eprint={2207.09918},
  primaryClass={cs-LG},
  note={arXiv:2207.09918}
  url={https://arxiv.org/abs/2207.09918}
}