Implementation of matrix factorization based on minimizing quasi-absolute distance for electromagnetic global signal elimination

Anomalous environmental electromagnetic (EM) radiation waves have been reported as the portents of earthquakes. We have been measuring the Extremely Low Frequency (ELF) range all over Japan. Our goal is to predict earthquakes using EM radiation waves. The recorded data often contain signals unrelated to earthquakes. These signals, as noise, confound earthquake prediction efforts. It is necessary to eliminate noises from observed signals in a preprocessing step. In previous researches, we used ISRA, an algorithm of the Non-negative Matrix Factorization (NMF), to estimate source signal. However, ISRA is not robust for outliers because ISRA´s cost function is based on square distance. In order to improve robustness, we should use lower order cost function. In this paper, we propose matrix factorization method based on quasi-absolute distance for global signal elimination.