A Reliable Online Dictionary Learning Denoising Strategy for Noisy Microseismic Data-Reference-Cited by-同舟云学术

A Reliable Online Dictionary Learning Denoising Strategy for Noisy Microseismic Data

Published:2023 Issue: Volume:61 Page:1-10
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

He Jian¹,Li Huailiang²^ORCID,Tuo Xianguo³,Wen Xiaotao¹^ORCID,Feng Liyuan¹

Affiliation:

1. Key Laboratory of Earth Exploration and Information Technology, Ministry of Education, Chengdu University of Technology, Chengdu, China

2. Key Laboratory of Earth Exploration and Information Technology, Ministry of Education, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China

3. School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China

Funder

National Natural Science Foundation of China

Distinguished Young Scholars Program of Sichuan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10056259.pdf?arnumber=10056259

Reference56 articles.

1. Semi‐Supervised Surface Wave Tomography With Wasserstein Cycle‐Consistent GAN: Method and Application to Southern California Plate Boundary Region

2. Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding

3. Automatic phase pickers: Their present use and future prospects

4. High‐Resolution Imaging of Complex Shallow Fault Zones Along the July 2019 Ridgecrest Ruptures

5. SEDENOSS: SEparating and DENOising Seismic Signals With Dual‐Path Recurrent Neural Network Architecture

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