EEMD Algorithm - Enhanced Version of EMD with MATLAB Implementation

This MATLAB code implements the Ensemble Empirical Mode Decomposition (EEMD) algorithm, an enhanced version of the Empirical Mode Decomposition (EMD) method developed by Huang in 2009. The algorithm addresses the critical issue of mode mixing in traditional EMD by incorporating white noise signals into the decomposition process. The implementation features noise-assisted data analysis where multiple EMD decompositions are performed on the original signal combined with different realizations of white noise. Key MATLAB functions include noise generation using randn(), ensemble averaging through multiple iterations, and the core EMD decomposition algorithm that extracts intrinsic mode functions (IMFs). Through ensemble averaging of the IMFs obtained from different noise-added signals, the EEMD algorithm effectively suppresses noise interference while preserving the true signal components. This approach significantly improves the handling of mode mixing phenomena in signal processing, leading to more accurate data analysis and processing outcomes. The code structure includes parameter configuration for noise amplitude and ensemble size, iterative decomposition loops, and result aggregation functions that combine the IMFs from multiple trials to produce the final clean decomposition.