Dynamic fuzzy clustering for infrasound as a precursor of earthquakes

Infrasonic airwaves offer a relatively unfiltered representation of source motions before an earthquake. It necessitates automatic processing of the infrasound as the precursor needs to be sorted before further analysis. An analysis of infrasonic records generated from five seismic case studies is provided in this article. Extracting the physical characters of different signals by signal processing such as Fourier Transform and Wavelets Transform are generally employed to carry out the necessary expansion. In this paper dynamic fuzzy clustering method is developed for classifying the set of multivariate infrasonic time trajectories from the unwanted infrasound sources.