Implementation of Short-Time Fourier Transform and Wigner Transform for Time-Frequency Distribution Algorithms

This program implements the Short-Time Fourier Transform (STFT) and Wigner Transform algorithms for time-frequency distribution analysis. STFT is a fundamental time-frequency analysis method that decomposes signals into time-frequency representations using sliding window techniques. The Wigner Transform represents another significant time-frequency distribution algorithm that provides high-resolution visualization of signal energy distribution across time and frequency domains. The primary objective of this implementation is to deliver an accessible and practical tool for time-frequency analysis and signal processing applications. Users can customize various parameters including window functions, window lengths, and overlap ratios for STFT, while adjusting resolution parameters for Wigner Transform calculations to achieve different analytical outcomes. Key implementation features include: - Sliding window mechanism with configurable Hanning/Hamming window functions - Fourier transform computation for each time segment - Bilinear transformation processing for Wigner distribution - Interactive parameter tuning interface The package includes comprehensive documentation and sample code demonstrating typical use cases such as: - Chirp signal analysis with varying frequency components - Multi-component signal separation techniques - Time-frequency resolution comparisons between methods - Practical applications in speech processing and vibration analysis These resources facilitate rapid learning and effective utilization for both educational and research purposes in signal processing domains.