MATLAB Source Code for S-Transform with Implementation Examples

MATLAB source code for S-transform implementation accompanied by several signal examples illustrating its usage and practical applications. As a relatively new technique in time-frequency analysis, S-transform has emerging applications in signal processing, seismic exploration, and speech recognition, making it a current research focus. The implementation demonstrates how S-transform can be applied to signal processing tasks such as noise reduction and feature extraction through time-frequency localization. In seismic exploration applications, the code shows how S-transform analyzes and interprets seismic signals by providing high-resolution time-frequency representations. For speech recognition, the implementation illustrates feature extraction and pattern recognition capabilities using speech signal examples. Beyond these domains, S-transform finds applications in image processing, medical signal analysis, and other fields where joint time-frequency information is crucial. The MATLAB code typically involves windowed Fourier transform implementation with frequency-dependent resolution, using algorithms that maintain phase information while providing absolute frequency reference. Mastering S-transform is essential for researchers and professionals working in these technical domains, particularly for developing advanced signal analysis applications.