Contributions to Proceedings:

P. Gerstoft, C. Mecklenbräuker, H. Yao:
"Bayesian Sparse Sensing of the Japanese 2011 Earthquake";
in: "46th Asilomar Conference of Signals, Systems, and Computing", IEEE Xplore, 2012, (invited), ISBN: 978-1-4673-5050-1, 281 - 285.

English abstract:
Sparse sensing is a technique for finding sparse signal repre- sentations to underdetermined linear measurement equations. We use sparse sensing to locate seismic sources during the rupture of the 2011 Mw9.0 earthquake in Japan from teleseis- mic P waves recorded by a seismic sensor array of stations in the United States. The location estimates of the seismic sources are obtained by minimizing the square of l2-norm of the difference between the observed and modeled waveforms penalized by the l1-norm of the seismic source vector. The resulting minimization problem is convex and can be solved efficiently using LASSO type optimization. The potential to track the rupture sequentially is demonstrated.

sparse reconstruction, lasso, compressive sensing, sensor signal processing

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.