Microseismic Signal Denoising and Separation Based on Fully Convolutional Encoder–Decoder Network

Microseismic Signal Denoising and Separation Based on Fully Convolutional Encoder–Decoder Network

Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method...

Full description

Bibliographic Details
Main Authors: Hang Zhang, Chunchi Ma, Veronica Pazzi, Yulin Zou, Nicola Casagli
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Applied Sciences
Subjects:
microseismic monitoring
deep learning
microseismic signal analysis
time–frequency domain
convolutional neural network
Online Access:https://www.mdpi.com/2076-3417/10/18/6621

Internet

https://www.mdpi.com/2076-3417/10/18/6621

Similar Items