Using a sparse model to evaluate the internal structure of impulse signals

Abstract

Impulse nature signals generated by complex geophysical systems require special methods to study their internal structure. These signals are characterized by a short duration of impulses and the variability of their structure. The use of classical spectral and time-frequency methods raises great difficulty. The authors propose a model of an impulse signal based on a sparse approximation and an algorithm for identifying a model. The algorithm is a modified matching pursuit algorithm using a physically based system of functions (dictionary). The study of modeling results consists in estimating the time-frequency characteristics of the model components. The paper gives an example of the model application on geoacoustic emission signals of a seismically active region (Kamchatka peninsula). The proposed model and approaches to the model investigation can be used for a wide range of impulse nature signals.