MATLAB Implementation of EMD Decomposition with Hilbert Spectral Analysis

This article demonstrates how to implement Empirical Mode Decomposition (EMD) for signal analysis and perform Hilbert spectral analysis on the original signal. EMD decomposition serves as a powerful signal processing technique that breaks down complex signals into multiple intrinsic mode functions (IMFs). The MATLAB implementation typically involves an iterative sifting process using functions like emd() to extract IMFs based on local extrema and envelope calculations. Following decomposition, Hilbert spectral analysis applied to each IMF reveals time-frequency characteristics through the hilbert() function, which computes the analytical signal for instantaneous frequency extraction. Both EMD decomposition and Hilbert spectral analysis offer practical, accessible methodologies that enable users with varying signal processing backgrounds to comprehend and implement these techniques efficiently. The code structure emphasizes straightforward implementation with proper visualization of IMF components and Hilbert spectrum plots using MATLAB's plotting functions.