HHT Hilbert Transform MATLAB Implementation for Beginners

This MATLAB program provides a comprehensive implementation of HHT (Hilbert-Huang Transform) specifically designed for beginners, helping users understand the algorithm's fundamentals and practical applications through clear code structure and detailed comments. The program includes the following key components with corresponding code implementations: 1. Data Preprocessing: Implements filtering and noise reduction techniques using MATLAB's signal processing toolbox functions (such as filtfilt() for zero-phase filtering) to prepare input data for HHT analysis, ensuring clean signal input for accurate transformation results. 2. Hilbert Transform: Utilizes MATLAB's built-in hilbert() function to perform the Hilbert transform on preprocessed data. The code demonstrates how to extract instantaneous frequency and amplitude values at each time point, with explanations of the analytical signal concept and its mathematical basis. 3. Instantaneous Frequency Analysis: The program includes plotting functions (plot() or stem()) to visualize instantaneous frequency variations over time, allowing observation of signal frequency characteristics and trends. Code comments explain frequency extraction methods from the Hilbert transform results. 4. Instantaneous Amplitude Analysis: Implements visualization of instantaneous amplitude time-series using MATLAB's graphing capabilities, enabling users to observe signal amplitude features and modulation patterns. The code demonstrates envelope detection techniques through the absolute values of analytic signals. 5. Result Visualization: Combines both frequency and amplitude analyses in comprehensive graphical outputs using subplot() arrangements, presenting results in clear chart formats suitable for beginner-level observation and interpretation. Includes labels, legends, and scaling for professional presentation. The program features well-structured, easily understandable code with extensive comments that explain HHT algorithm principles and implementation steps. Each section contains practical examples demonstrating proper function usage and parameter settings. This implementation aims to support learning and research by providing hands-on experience with time-frequency analysis techniques through MATLAB's computational environment.