141 citations · 281 across the 9 of their papers we have counts for
9 papers
Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot
A. Govinda Raj, J. H. McClellan
We address the problem of search-free DOA estimation from a single noisy snapshot for sensor arrays of arbitrary geometry, by extending a method of gridless super-resolution beamfo…
Deep learning for seismic phase detection and picking in the aftershock zone of 2008 Mw7.9 Wenchuan earthquake
Lijun Zhu, Zhigang Peng, James McClellan +4
The increasing volume of seismic data from long-term continuous monitoring motivates the development of algorithms based on convolutional neural network (CNN) for faster and more r…
Single Snapshot Super-Resolution DOA Estimation for Arbitrary Array Geometries
A. Govinda Raj, J. H. McClellan
We address the problem of search-free direction of arrival (DOA) estimation for sensor arrays of arbitrary geometry under the challenging conditions of a single snapshot and cohere…
Iterative interferometry-based method for picking microseismic events
Naveed Iqbal, Abdullatif A. Al-Shuhail, SanLinn I. Kaka +3
Continuous microseismic monitoring of hydraulic fracturing is commonly used in many engineering, environmental, mining, and petroleum applications. Microseismic signals recorded at…
Joint Seismic Data Denoising and Interpolation with Double-Sparsity Dictionary Learning
Lingchen Zhu, Entao Liu, James H. McClellan
Seismic data quality is vital to geophysical applications, so methods of data recovery, including denoising and interpolation, are common initial steps in the seismic data processi…
A multi-channel approach for automatic microseismic event association using RANSAC-based arrival time event clustering(RATEC)
Lijun Zhu, Lindsay Chuang, James H. McClellan +2
In the presence of background noise, arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location esti…