Abstract
Reliable seismic waves characterization is essential for better understanding wave propagation phenomena, providing new physical insight into soil properties. Many works in this area have been based on detecting special patterns or clusters in seismic data, event detection using parametric models, and time-frequency analysis. In this paper we present an approach making use of the short-term time-frequency Rényi entropy and maximum a posteriori probability (MAP) estimator, operating on Rényi entropy, as a new space of decision; this method enables more robust feature extraction and a more accurate classification. This approach was used in simulation and in the analysis of the earthquake records during the Kocaeli, Arcelik seism, Turkey, August 1999, a strong to moderate ground motion.
87.57.nm, 43.60.Hj, 89.70.Cf, 02.50.-r, 91.30.-f.
Keywords: Maximum a posteriori probability, Rényi entropy, seismic signals, signal segmentation, time-frequency.
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