Skip to content

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

Notifications You must be signed in to change notification settings

shankarchawla1776/ECG_GAN_MBD

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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}
}

About

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

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%