Several Implementations of Short-Time Fourier Transform

The following MATLAB code demonstrates several implementations of Short-Time Fourier Transform (STFT). These code examples are designed to help users better understand and learn this fundamental signal processing algorithm. Before downloading the code, let's briefly review the STFT concept. Short-Time Fourier Transform is a crucial signal processing technique that decomposes signals into their frequency components over time, enabling comprehensive time-frequency analysis. It finds extensive applications in various domains including audio processing, image analysis, and video processing. In MATLAB, STFT can be implemented using different approaches. One common method utilizes window functions to extract localized frequency information from signals. The implementation typically involves: - Segmenting the signal using overlapping windows (Hamming, Hanning, or Gaussian windows) - Applying Fourier transform to each windowed segment - Constructing a spectrogram from the transformed segments Key MATLAB functions involved in these implementations include spectrogram(), stft(), and custom implementations using fft() with windowing operations. The code provides examples of different parameter configurations, including various window sizes, overlap ratios, and frequency resolution settings. For those new to STFT, we recommend studying fundamental signal processing tutorials first. For experienced users looking to explore different STFT variations and implementation techniques, downloading these MATLAB codes serves as an excellent starting point for advanced study and practical application development.