Explore MATLAB source code curated for "STFT" with clean implementations, documentation, and examples.
Short-Time Fourier Transform (STFT) source code for time-frequency joint analysis of non-stationary signals, ready to use in MATLAB programs without extraction password. Includes practical implementation with windowing functions and spectral computation.
Comparative time-frequency analysis of transient signals using Short-Time Fourier Transform (STFT), Wavelet Transform, and Empirical Mode Decomposition (EMD) with code implementation insights
Windowed transformation technique demonstrating Short-Time Fourier Transform (STFT) using Gaussian window functions with different scaling parameters, showing how window function variations impact time-frequency analysis results.
Utilizing four-component Gaussian envelope signals for time-frequency analysis, comparing resolution and cross-term interference among STFT, WVD, and CWD methods. Includes simulation code and MATLAB time-frequency analysis toolbox with implementation notes. Toolbox usage recommendations reference "MATLAB Time-Frequency Analysis Technology and Its Applications - Ge Zhexue", with the book's source code included in the package for practical integration.
Implementation of Short-Time Fourier Transform (STFT) based spectrogram plotting in MATLAB environment
Discrete Short-Time Fourier Transform function for 1D vectors. Function name: stft, Input: one-dimensional array to be processed, Windowing: rectangular window, Window width: 20 samples. Implementation handles signal segmentation with overlapping windows and computes frequency-domain representation.
3D surface visualization of Wigner-Ville Distribution for frequency-hopping signals, including STFT-based time-frequency analysis and spectrogram generation of Wigner-Ville Distribution for FH signals
This project implements hop period estimation for frequency-hopping signals using STFT (Short-Time Fourier Transform). The process involves simulating a frequency-hopping signal, analyzing it through STFT to obtain a time-frequency matrix, extracting the time plane, removing DC components from the time series, performing Fourier transformation, and ultimately calculating the hop period. The implementation includes key signal processing functions such as windowing, spectral analysis, and peak detection algorithms.
Comprehensive comparison of FFT and STFT algorithms using MATLAB with code implementation details and spectral analysis demonstrations
A comprehensive STFT example with duration 1000, sampling rate 250, demonstrating Short-Time Fourier Transform (STFT) signal processing technique for time-frequency analysis