Complete EMD (Empirical Mode Decomposition) Program - 2005 Version

This documentation presents the 2005 version of the complete Empirical Mode Decomposition (EMD) program, a sophisticated signal processing method designed for analyzing complex data signals. The algorithm systematically decomposes intricate signals into multiple Intrinsic Mode Functions (IMFs), where each IMF represents distinct scale and frequency components within the original signal. The implementation features an iterative sifting process that identifies local extrema, constructs envelope functions using cubic spline interpolation, and extracts IMF components meeting the following criteria: symmetric envelope, zero mean, and equal number of zero-crossings and extrema. Key algorithmic components include: - Local extrema detection for identifying signal peaks and troughs - Envelope construction using spline interpolation - Mean envelope calculation and iterative sifting - Stopping criterion implementation based on standard deviation thresholds - IMF validation and residue extraction By utilizing this 2005 EMD implementation, researchers can effectively analyze signal characteristics, identify underlying patterns, and extract meaningful frequency components from complex datasets. The program supports various signal processing applications including biomedical signal analysis, financial data decomposition, and mechanical vibration studies.