Windowed Fourier Transform Source

The Windowed Fourier Transform is a fundamental technique for analyzing signal spectral characteristics. In MATLAB, this transformation can be implemented using built-in functions or custom scripts. The core concept involves applying specific window functions to signals to reduce spectral leakage and enhance frequency resolution.

The implementation approach typically follows these steps: First, segment the input signal and multiply each data segment with a selected window function (such as Hanning, Hamming, or rectangular window). Then perform a Fast Fourier Transform (FFT) on the windowed signal to obtain local spectral information. By adjusting the window type and length, users can balance frequency resolution and spectral leakage sensitivity. In MATLAB, this can be achieved using the fft() function combined with window generation tools like hann() or hamming().

For higher precision applications, custom window functions or overlapping segmentation methods can be implemented to optimize analysis results. The Windowed Fourier Transform is particularly suitable for time-frequency analysis of non-stationary signals, such as audio processing and vibration signal detection. Key MATLAB functions include fft() for Fourier transformation, window() for window generation, and spectrogram() for advanced time-frequency analysis with built-in windowing capabilities.