An ECG Denoising Method Based on the Generative Adversarial Residual Network

Figure 4

The adversarial learning process of the GAN model. This figure can be understood as (a) an adversarial pair close to convergence, similar to and . The discriminator is used to judge whether the two distributions are the same. Then, the discriminator is trained. As shown in (b), the discriminator is continuously improving the ability to identify a clean ECG signal and denoising the raw ECG signal. In (c), as the adversarial progresses, the signal generated by the generator gradually approaches the original clean signal received in the discrimination. In (d), through enough feedback, the generator has the ability to compete with the discriminator.

(a)

(b)

(c)

(d)