Weak periodic signal identification in low amplitude seismic waves based on chaotic oscillator

Abstract This study aims to identify weak periodic or quasi-periodic signals within seismic data, as these low-amplitude signals provide valuable insights into seismic dynamics but are often masked by chaotic noise. To address this challenge, we employ a novel detection method based on the Duffing oscillator, a tool well-suited for analyzing complex, noisy systems. Applying this approach to seismic data from two moderate earthquakes, we successfully extract weak periodic and quasi-periodic signals embedded within the noise. The results reveal distinct signal patterns that reflect the dynamics of the fault segments associated with the analyzed earthquakes. These findings demonstrate the effectiveness of chaos-based methods in seismic signal detection and highlight their potential for improving real-time seismic monitoring and prediction. More broadly, this work contributes to the understanding of chaos and complexity in natural systems, offering new perspectives for the study of seismic activity.