Nonstationary signal decomposition for dummies

TL;DR

This paper provides a concise survey of methods for decomposing nonstationary signals, comparing classical techniques like Fourier and wavelet transforms with recent approaches, to guide practitioners in choosing suitable methods.

Contribution

It offers a self-contained overview of nonstationary signal decomposition methods, highlighting recent advancements and their advantages over classical techniques.

Findings

Recent methods improve adaptability to nonstationarity

Classical methods like Fourier and wavelet have limitations

Survey aids in selecting appropriate decomposition techniques

Abstract

How can I decompose a nonstationary signal? What are the advantages of using the most recent methods available in the literature versus using classical methods like (short time) Fourier transform or wavelet transform? This paper tries to address these and other questions providing the reader with a brief and self contained survey on what and how to tackle the decomposition of nonstationary signals.