Global and Local Scale High-Resolution Seismic Event Catalogs for Algorithm Development and Testing
Abstract not provided.
Publications
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Jump to search filtersTracking scattered signals in the acoustic coda using independent component analysis in a topographically complex setting
Geophysical Journal International
We outline a method using gradient flow independent component analysis (ICA) to separate signals comprising the coda in a topographically complex setting.We also identify the sources of scattered signals by tracking signal backazimuths over time. The gradient flow ICA method is shown to effectively separate signals in the acoustic coda. The method correctly identifies the backazimuth of the first arrival from two 800 kg TNT equivalent explosions as well as subsequent signals scattered by the surrounding topography. Circular statistics is used to analyse the variance, mean and uniformity of calculated backazimuths. These results have strong implications for understanding the acoustic wavefield by identifying scatterers and inverting for atmospheric conditions.
Seismic and Infrasound Reference Data Sets
Abstract not provided.
Unlocking Real Time Infrasound Event Classification Abilities Using Machine Learning
Abstract not provided.
Infrasound Event Classification: A Comparison of Machine Learning Approaches
Abstract not provided.
Infrasound Event Categorization Using Machine Learning and Deep Learning
Abstract not provided.
Classification of Local Seismic Events in the Utah Region: A Comparison of Amplitude Ratio Methods with a Machine Learning Approach
Abstract not provided.
Seismic Phase Identification with a Merged Deep Neural Network
Abstract not provided.
Semi-Supervised Classification of Seismic Events in an Inaccessible Region
Abstract not provided.
Unlocking Real Time Infrasound Event Classification Abilities Using Machine Learning
Abstract not provided.
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