Shape-adaptive Mode Decomposition (SAMD) in Matlab: Hands-on Tutorial

In this hands-on tutorial series, we explore how to use the Matlab implementation of SAMD (shape-adaptive mode decomposition), combined with synchrosqueezing transform (SST) and de-shape synchrosqueezing transform (ds-SST). The Matlab code can be downloaded here: https://www.dropbox.com/scl/fi/4mixzq27c2sdjhjanq9uy/ShareSAMDcodeSimulation-Lecture4-20250413.zip?rlkey=94hl2unmwqvcbm9qtgw92fgpg&dl=0 This lecture is designed for hands-on researchers, engineers, and students who need to apply time-frequency analysis techniques to analyze their nonstationary time series data, particularly those with complicated oscillatory patterns. In this lecture, We will cover (1) how to apply SAMD to decompose a non-sinusoidal oscillatory signal into its non-sinusoidal oscillatory components. We focus on the simulated signals in this lecture. In the next lecture, we will continue with real data.