High precious time synchronization based on denoising autoencoder

In synchronized communication systems, precise time synchronization is a crucial guarantee for ensuring the accuracy of data reception. However, in practice, time synchronization between two locations often exhibits certain frequency or phase drifts. To address this problem, our paper proposes a denoising autoencoder based on neural network to compensate for the time deviations introduced by external factors. Our results demonstrate that this method effectively reduces sampling errors, equivalently improving the system's time synchronization accuracy. This method not only provides an effective solution for enhancing time synchronization precision but also lays the foundation for time synchronization performance in the future.