2D Hybrid method:Case of VLF signal amplitude variations in the time vicinity of an earthquake

TL;DR

This paper introduces a 2D Hybrid wavelet-based method to detect oscillations in noisy natural data, demonstrated on VLF signals near an earthquake, revealing a specific oscillation linked to the seismic event.

Contribution

The paper presents a novel 2D Hybrid wavelet approach that enhances resolution and detects directional changes in oscillations within noisy data sets, applied to earthquake-related signals.

Findings

Detected a 120-130 s oscillation associated with the earthquake

Method improves resolution of oscillations in the period plane

Identified signal direction using correlation coefficients

Abstract

Extraction of information in the form of oscillations from noisy data of natural phenomena such as sounds, earthquakes, ionospheric and brain activity, and various emissions from cosmic objects is extremely difficult. As a method for finding periodicity in such challenging data sets, the 2D Hybrid approach, which employs wavelets, is presented. Our technique produces a wavelet transform correlation intensity contour map for two (or one) time series on a period plane defined by two independent period axes. Notably, by spreading peaks across the second dimension, our method improves apparent resolution of detected oscillations in the period plane and identifies the direction of signal changes using correlation coefficients. We demonstrate the performance of the 2D Hybrid technique on a very low frequency (VLF) signal emitted in Italy and recorded in Serbia in time vicinity of the occurrence of an earthquake on November 3, 2010, near Kraljevo, Serbia. We identified a distinct signal in the range 120-130 s that appears only in association with the considered earthquake. Other wavelets, such as Superlets, which may detect fast transient oscillations, will be employed in the future analysis.