Short-Time Fourier Transform and Wavelet Transform with MATLAB Implementation

The Short-Time Fourier Transform (STFT) and Wavelet Transform can be implemented using MATLAB programming language. These transformation methods are essential tools in signal processing for analyzing spectral characteristics and time-frequency properties of signals. MATLAB provides built-in functions such as spectrogram() for STFT implementation, which computes the Fourier transform of windowed signal segments with parameters like window size, overlap, and sampling frequency. For wavelet transform, MATLAB's Wavelet Toolbox offers functions including cwt() for continuous wavelet analysis and dwt() for discrete wavelet decomposition, supporting various wavelet families (Daubechies, Coiflets, etc.). The implementation involves defining signal parameters, selecting appropriate window functions (Hamming, Hanning) for STFT, choosing wavelet types and scales for wavelet analysis, and visualizing results using time-frequency plots and scalograms. Comprehensive documentation accompanies the code, detailing implementation steps, parameter configuration guidelines, and practical usage examples for both time-frequency analysis techniques.