Short-Time Fourier Transform (STFT)

This article introduces a tool for computing the Short-Time Fourier Transform (STFT). Notably, STFT is a signal processing technique that decomposes non-stationary signals into time-localized windowed segments. This method is widely applied in signal processing domains such as audio signal analysis and image processing. The implementation typically involves sliding a window function (e.g., Hann or Hamming window) through the signal and computing the Fourier transform for each windowed segment. Key parameters include window size, overlap percentage, and window type selection, which directly affect time-frequency resolution trade-offs. This tool plays a crucial role in processing such signals by enabling time-frequency representation analysis. Additionally, it facilitates examination of signal frequency components and phase information through spectrogram visualization. The algorithm generally follows these steps: 1) Segment the signal using overlapping windows, 2) Apply window function to reduce spectral leakage, 3) Compute FFT for each frame, 4) Aggregate results into a time-frequency matrix. In summary, this tool enhances understanding of signal characteristics and expands capabilities in signal processing applications through programmable control over analysis parameters.