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Signal segmentation in time-frequency plane using Rényi entropy - Application in seismic signal processing

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 a new approach making use of the short-term time-frequency Rényi entropy and maximum a posteriori probability (MAP) estimator, operating on time-frequency 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.