# Application of the Huang-Hilbert transform and natural time to the analysis of Seismic Electric Signal activities

## TL;DR

This paper combines the Huang-Hilbert transform and natural time analysis to improve the identification of Seismic Electric Signals by decomposing signals into intrinsic modes and distinguishing them from noise.

## Contribution

It introduces a novel approach integrating Huang-Hilbert transform with natural time analysis for better SES characterization and noise discrimination.

## Key findings

- IMFs' instantaneous amplitudes help distinguish SES from noise
- Natural time analysis enhances SES detection accuracy
- Huang-Hilbert transform effectively decomposes SES signals

## Abstract

The Huang-Hilbert transform is applied to Seismic Electric Signal (SES) activities in order to decompose them into a number of Intrinsic Mode Functions (IMFs) and study which of these functions better represent the SES. The results are compared to those obtained from the analysis in a new time domain termed natural time after having subtracted the magnetotelluric background from the original signal. It is shown that the instantaneous amplitudes of the IMFs can be used for the distinction of SES from artificial noises when combined with the natural time analysis.