STFTbased

STFTbased refers to methods or analyses that utilize the Short-Time Fourier Transform (STFT) as their primary technique. The STFT is a signal processing technique used to determine the sinusoidal frequency and phase content of a signal over time. It works by breaking down a longer signal into smaller segments of equal length, and then performing a Fourier Transform on each segment. This allows for the analysis of how the frequency content of a signal changes over time, which is particularly useful for non-stationary signals, meaning signals whose frequency content varies over time.

Common applications of STFTbased approaches include audio processing, where it's used for tasks like spectral analysis, pitch detection, and noise reduction. In speech recognition, STFTbased features like Mel-frequency cepstral coefficients (MFCCs) are fundamental. The STFT is also employed in vibration analysis to identify resonant frequencies that may change during operation, and in medical signal processing for analyzing biological signals such as electrocardiograms (ECGs) or electroencephalograms (EEGs). The STFT essentially provides a time-frequency representation, often visualized as a spectrogram, which is a powerful tool for understanding dynamic signal behavior. The choice of window size and overlap in the STFT is crucial, as it affects the time and frequency resolution trade-off.