Ensemble Empirical Mode Decomposition (EEMD) - Optimized Implementation

The EEMD function referenced in the documentation has been systematically adjusted and optimized for enhanced performance and usability. This implementation features noise-assisted data analysis through multiple ensemble trials, where added white noise facilitates proper mode separation. The algorithm automatically handles the sifting process for intrinsic mode function (IMF) extraction with adaptive stopping criteria. Key implementation details include configurable parameters for ensemble size, noise amplitude, and maximum sifting iterations. The function returns a matrix of IMF components along with residual trend, supporting signal decomposition applications in noise reduction, feature extraction, and time-frequency analysis. Optimizations ensure numerical stability through mirror extension for boundary effects and implement energy difference thresholding for sifting termination. The code structure allows direct integration with signal processing workflows while maintaining computational efficiency through vectorized operations.