A Generative Adversarial Approach To ECG Synthesis And Denoising

Generative Adversarial Networks (GAN) are known to produce synthetic data that are difficult to discern from real ones by humans . In this paper, we present an approach to use GAN to produce realistically looking ECG signals… We utilize them to train and evaluate a denoising autoencoder that achieves state-of-the-art filtering quality . It is demonstrated that generated data improves the model performance compared to the model trained on real data only .

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Keywords : data - denoising - approach - adversarial - gan -

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