EMD MATLAB Program with Test Data

Application Background: Empirical Mode Decomposition (EMD) is a time-frequency analysis method designed for processing nonlinear and non-stationary signals. A key feature of this method is its ability to adaptively decompose input signals into a sum of Intrinsic Mode Functions (IMFs) based solely on the signal's intrinsic characteristics, without requiring any prior knowledge. EMD finds widespread applications in signal denoising, non-stationary time series prediction, and related fields, providing effective solutions for these applications. Key Technology: The EMD algorithm achieves denoising, analysis, and prediction capabilities for high-frequency signals through decomposition and trend analysis. The MATLAB implementation generally follows these steps: 1. Identify all local extrema in the input signal 2. Construct upper and lower envelopes using cubic spline interpolation 3. Calculate the mean envelope and extract the detail component 4. Repeat the sifting process until IMF criteria are met 5. Separate residual trends from oscillatory components This algorithm significantly improves the accuracy and efficiency of signal processing, providing crucial support for research and applications in related domains.