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This repository is for the paper "Synthesis of Realistic ECG using Generative Adversarial Networks".

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ECG_GAN_MBD

This repository is for the paper "Synthesis of Realistic ECG using Generative Adversarial Networks".

The current files uploaded are for implementing Minibatch Discrimination (MBD) for a 2 Layer CNN discriminator, please note that for ECG data with MBD layers the training does not converge.

You can edit the Model.py file accordingly to remove MBD layers and/or to add more Convolution-Pooling layer as described in the paper.

Usage: $python3 train.py


Citation

If you find this repo helpful in any way please cite our arXiv preprint:

@misc{delaney2019synthesis,
  title={Synthesis of Realistic ECG using Generative Adversarial Networks},  
  author={Anne Marie Delaney and Eoin Brophy and Tomas E. Ward},
  year={2019},
  eprint={1909.09150},
  archivePrefix={arXiv},
  primaryClass={eess.SP}
}

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This repository is for the paper "Synthesis of Realistic ECG using Generative Adversarial Networks".

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