Time-Frequency Analysis of Signals using Short-Time Fourier Transform and Wigner-Ville Distribution

This MATLAB program performs advanced time-frequency analysis of signals using two powerful techniques: Short-Time Fourier Transform (STFT) and Wigner-Ville Distribution (WVD). The implementation begins with STFT processing, which employs a sliding window approach to analyze signal frequency content across time segments. The algorithm typically uses MATLAB's spectrogram function with configurable parameters including window size, overlap percentage, and FFT length to achieve optimal time-frequency resolution trade-offs. Following the STFT analysis, the program computes the Wigner-Ville Distribution, a bilinear time-frequency representation that provides superior resolution compared to linear transforms. The WVD implementation handles cross-term interference through appropriate windowing techniques while maintaining high concentration in the time-frequency plane. Key functions involved include signal preprocessing, Hilbert transform for analytic signal generation, and customized WVD computation routines that manage the quadratic nature of the distribution. Through this comprehensive analysis toolkit, researchers can obtain detailed insights into signal spectral characteristics, transient behaviors, and time-varying frequency components. The program enables comparative assessment of both methods, facilitating deeper understanding of signal properties for applications in signal processing, communications, and vibration analysis. The code includes visualization components for plotting time-frequency contours, spectral density maps, and comparative analysis results.