Iterative Gaussian mixture model and multi‐channel attributes for arrival picking in extremely noisy environments-Reference-Cited by-同舟云学术

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Iterative Gaussian mixture model and multi‐channel attributes for arrival picking in extremely noisy environments

Published:2021-12-22 Issue:2 Volume:70 Page:343-361
ISSN:0016-8025
Container-title:Geophysical Prospecting
language:en
Short-container-title:Geophysical Prospecting

Author:

Wang Hang¹^ORCID,Chen Yangkang²^ORCID

Affiliation:

1. School of Earth Sciences Zhejiang University Zheda Road, No. 38 Hangzhou Zhejiang Province 310058 China

2. Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences The University of Texas at Austin Box X Austin TX 78758 USA

Publisher

Wiley

Subject

Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2478.13164

Reference47 articles.

1. Automatic earthquake recognition and timing from single traces

2. An Automatic P-Phase Picking Algorithm Based on Adaptive Multiband Processing

3. Local singular value decomposition for signal enhancement of seismic data

4. Optimization approach to automatic first arrival picking for three-component three-dimensional vertical seismic profiling data

5. Fast waveform detection for microseismic imaging using unsupervised machine learning

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1. Automatic first break picking with structured random forests;Geophysical Prospecting;2023-07-10

2. Urban DAS Data Processing and Its Preliminary Application to City Traffic Monitoring;Sensors;2022-12-18

3. Automatic Time Picking for Weak Seismic Phase in the Strong Noise and Interference Environment: An Hybrid Method Based on Array Similarity;Sensors;2022-12-16

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