Parameter Estimation of Two-Component Superposed Decaying Oscillation Signal Using Autoencoders

Abstract

We discuss parameter estimation of decaying oscillations using autoencoders. Decaying oscillations commonly occur in many physical systems and analyzing them can reveal the characteristics of the underlying physics. Rapidly decaying signals are challenging to analyze using conventional methods, and observational data often contain noise. Under such conditions, machine learning offers the potential for efficient and high-precision parameter estimation. In this study, we utilize the latent space of autoencoders to estimate the frequency, phase, decay time, amplitude of decaying oscillations in noise, and evaluate the estimation accuracy.