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

• DOI

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.

Kim A.A., Lukovenkova O.O., Marapulets Yu.V., Tristanov A.B. Using a sparse model to evaluate the internal structure of impulse signals // 2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 19-21 Sept. 2018, Poznan, Poland. IEEE.