Peter Gerstoft's starred repositories
sound-field-neural-network
A deep-learning-based method for sound field reconstruction
IntroToDASData
a friendly introduction to reading and working with DAS data
Untrained-PINN-for-SIM
Untrained, physics-informed neural network for SIM image reconstruction
acoustic_gps
Gaussian processes for sound field reconstruction
locally-sparse-tomography
Locally sparse travel time tomography (LST) is a tomography algorithm which uses sparse modeling and dictionary learning to estimate 2D geophysical images based on wave travel times across sensor arrays. This repository is an implementation of the IEEE paper: M.J. Bianco and P. Gerstoft, "Travel time tomography with adaptive dictionaries," IEEE Trans. on Computational Imaging, Vol. 4, No. 4, 2018.
RISCluster
Deep clustering for seismic signals (icequakes and earthquakes)
acs-sp-demos
Acoustic signal processing demos with jupyter notebooks
SoundMapping-ODAS
This repository is created to document any scripts that are made under the supervision of Prof. Yoav Freund and Prof. Peter Gerstoft in the process of creating a sound data processing and analyzing project
Array_codes
Hinet and LASA beamforming codes
OceanAcoustic_Ranging_MachineLearning
A repo originally developed for UCSD course SIO 209. This work is developed directly from the publications Niu, Reeves, Gerstoft (2017a) and Niu, Ozanich, Gerstoft (2017b):