MATLAB Implementation for Non-Stationary Signal Analysis

Non-stationary signal analysis is a methodology for investigating the characteristics of signals whose statistical properties vary over time. This approach involves using the Short-Time Fourier Transform (STFT) for signal analysis, which can be implemented in MATLAB through functions like spectrogram() with configurable window size and overlap parameters to balance time-frequency resolution. Additionally, advanced techniques such as Gabor Expansion (implementable via gaborgabor function for multi-resolution analysis), Choi-Williams Distribution (using time-frequency toolbox functions to reduce cross-term interference), and Wigner-Ville Distribution (employing wvd() for high-resolution time-frequency representation despite potential cross-terms) provide deeper analytical capabilities. These MATLAB implementations typically involve signal preprocessing, parameter optimization for kernel functions, and visualization using contour plots or spectrograms. Through these analytical methods, researchers can gain comprehensive insights into the temporal evolution of frequency components and behavioral patterns of non-stationary signals.