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Bayesian sparse sensing of the Japanese 2011 earthquake

机译:贝叶斯稀疏的日本2011地震的感觉

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摘要

Sparse sensing is a technique for finding sparse signal representations 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 teleseismic 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.
机译:稀疏感测是用于找到稀疏信号表示到未确定的线性测量方程的技术。 我们使用稀疏感应来定位在日本2011 MW9.0地震的破裂期间从美国遭受地震传感器站记录的Telesmicic P波在日本破裂期间定位地震来源。 通过最小化&#x2113的平方来获得地震源的位置估计; 2 norm的观察和建模的波形之间的差异,由&#x2113惩罚; 1 -norm的地震源矢量。 由此产生的最小化问题是凸的,可以使用套索型优化有效地解决。 证明了跟踪破裂的可能性。

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