Enhanced Hilbert-Huang Transform

This section elaborates on the enhanced Hilbert-Huang Transform (HHT) methodology and its MATLAB implementation specifics. The improved HHT serves as a powerful signal processing technique for time-frequency analysis, enabling effective extraction of critical signal characteristics. MATLAB implementation involves three key phases: signal preprocessing using functions like detrend() and filter() to remove noise and baseline wander, core HHT algorithm execution through empirical mode decomposition (EMD) with enhanced sifting processes using MATLAB's while loops and interpolation functions, and post-processing with Hilbert spectral analysis via hilbert() function for instantaneous frequency calculation. The MATLAB realization facilitates deeper understanding of HHT's underlying principles—particularly the adaptive decomposition mechanism for non-stationary signals—while demonstrating practical applications through customizable parameters like stopping criteria thresholds and IMF component selection. This implementation framework allows researchers to adapt the enhanced HHT for diverse real-world scenarios including biomedical signal analysis and mechanical vibration monitoring.