Short-Time Fourier Transform (STFT)

This program implements the Short-Time Fourier Transform (STFT) algorithm, which decomposes signals into different frequency components over time windows. The core algorithm involves applying a sliding window to segment the signal into short time frames, followed by Fourier Transform analysis for each frame. This approach enables time-frequency localization, revealing how signal frequencies evolve over time. STFT finds extensive applications in signal processing fields including audio analysis (voice activity detection, music transcription), image processing (texture analysis), and vibration analysis. Key implementation considerations include window function selection (Hamming/Hanning windows), window size optimization for time-frequency resolution trade-offs, and overlap-add reconstruction techniques. For code implementation, typical functions include frame segmentation using sliding windows, window function application, FFT computation per frame, and spectrogram visualization. Mastering STFT is essential for professionals working with non-stationary signal analysis. We welcome feedback and technical questions regarding the implementation details or potential enhancements to this STFT codebase.