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torchsignal: a signal processing library for PyTorch

The torchsignal package consists of datasets, model architectures, and common signal processing functions before applying on PyTorch. A toolbox for data manipulation and transformation for signal processing.


Currently, this has not been released. Use Git or checkout with SVN, and install the dependencies:

git clone
pip install -r requirements.txt


See requirements.txt.


See the examples folder.


These are the models available in this repo:

  • Multitask Model
  • EEGNet
  • Performer
  • WaveNet

See list of models and usage.

API Reference

Work in progress. Meanwhile see the examples folder.


We aim to bridge the gap for anyone who are new signals processings to get started.

Contributing Guidelines

Please let us know if you encounter a bug by filing an issue.

Seeking for collaborators to contribute new features, utility functions, bug fixes, and documentation. Currently, I am working on this alone. If you are working on signal processing or brain-computer interface, and keen to build a high-quality package to apply PyTorch to the signal processing domain, reach out to me via various channels.

Disclaimer on Datasets

We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have license to use the dataset. It is your responsibility to determine whether you have permission to use the dataset under the dataset's license.

If you're a dataset owner and wish to update any part of it (description, citation, etc.), or do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thanks for your contribution to the ML community!

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